From 4fb0a52e67576cbc0b339978e3ddb5bdb8b0fcb3 Mon Sep 17 00:00:00 2001 From: samanta-sc Date: Sat, 8 Nov 2025 19:09:28 +0600 Subject: [PATCH 1/3] Solved TypeError: unsloth_push_to_hub_gguf() got multiple values for argument 'repo_id' when tried to push GGUF version to HuggingFace --- nb/Gemma3N_(4B)-Audio.ipynb | 55 +++-- nb/Gemma3N_(4B)-Conversational.ipynb | 193 ++++++++++-------- nb/Gemma3_(1B)-GRPO.ipynb | 168 ++++++++------- nb/Gemma3_(270M).ipynb | 170 ++++++++------- nb/Gemma3_(27B)_A100-Conversational.ipynb | 37 ++-- nb/Gemma3_(4B).ipynb | 168 ++++++++------- nb/HuggingFace Course-Gemma3_(1B)-GRPO.ipynb | 168 ++++++++------- nb/Kaggle-Gemma3N_(4B)-Audio.ipynb | 50 +++-- nb/Kaggle-Gemma3N_(4B)-Conversational.ipynb | 188 +++++++++-------- nb/Kaggle-Gemma3_(1B)-GRPO.ipynb | 153 +++++++------- nb/Kaggle-Gemma3_(270M).ipynb | 165 ++++++++------- ...gle-Gemma3_(27B)_A100-Conversational.ipynb | 32 +-- nb/Kaggle-Gemma3_(4B).ipynb | 163 ++++++++------- original_template/Gemma3N_(4B)-Audio.ipynb | 3 +- .../Gemma3N_(4B)-Conversational.ipynb | 3 +- original_template/Gemma3_(1B)-GRPO.ipynb | 3 +- original_template/Gemma3_(270M).ipynb | 5 +- .../Gemma3_(27B)_A100-Conversational.ipynb | 3 +- original_template/Gemma3_(4B).ipynb | 3 +- python_scripts/Gemma3N_(4B)-Audio.py | 3 +- python_scripts/Gemma3N_(4B)-Conversational.py | 3 +- python_scripts/Gemma3_(1B)-GRPO.py | 3 +- python_scripts/Gemma3_(270M).py | 3 +- .../Gemma3_(27B)_A100-Conversational.py | 3 +- python_scripts/Gemma3_(4B).py | 3 +- .../HuggingFace Course-Gemma3_(1B)-GRPO.py | 3 +- python_scripts/Kaggle-Gemma3N_(4B)-Audio.py | 3 +- .../Kaggle-Gemma3N_(4B)-Conversational.py | 3 +- python_scripts/Kaggle-Gemma3_(1B)-GRPO.py | 3 +- python_scripts/Kaggle-Gemma3_(270M).py | 3 +- ...Kaggle-Gemma3_(27B)_A100-Conversational.py | 3 +- python_scripts/Kaggle-Gemma3_(4B).py | 3 +- 32 files changed, 969 insertions(+), 800 deletions(-) diff --git a/nb/Gemma3N_(4B)-Audio.ipynb b/nb/Gemma3N_(4B)-Audio.ipynb index adffef71..17726d09 100644 --- a/nb/Gemma3N_(4B)-Audio.ipynb +++ b/nb/Gemma3N_(4B)-Audio.ipynb @@ -8,7 +8,7 @@ "
\n", "\n", "\n", - " Join Discord if you need help + \u2b50 Star us on Github \u2b50\n", + " Join Discord if you need help + ⭐ Star us on Github ⭐\n", "
\n", "\n", "To install Unsloth your local device, follow [our guide](https://docs.unsloth.ai/get-started/install-and-update). This notebook is licensed [LGPL-3.0](https://github.com/unslothai/notebooks?tab=LGPL-3.0-1-ov-file#readme).\n", @@ -51,7 +51,22 @@ "execution_count": null, "metadata": {}, "outputs": [], - "source": "%%capture\nimport os, re\nif \"COLAB_\" not in \"\".join(os.environ.keys()):\n !pip install unsloth\nelse:\n # Do this only in Colab notebooks! Otherwise use pip install unsloth\n import torch; v = re.match(r\"[0-9\\.]{3,}\", str(torch.__version__)).group(0)\n xformers = \"xformers==\" + (\"0.0.32.post2\" if v == \"2.8.0\" else \"0.0.29.post3\")\n !pip install --no-deps bitsandbytes accelerate {xformers} peft trl triton cut_cross_entropy unsloth_zoo\n !pip install sentencepiece protobuf \"datasets>=3.4.1,<4.0.0\" \"huggingface_hub>=0.34.0\" hf_transfer\n !pip install --no-deps unsloth\n!pip install transformers==4.56.2\n!pip install --no-deps trl==0.22.2\nimport torch; torch._dynamo.config.recompile_limit = 64;\n" + "source": [ + "%%capture\n", + "import os, re\n", + "if \"COLAB_\" not in \"\".join(os.environ.keys()):\n", + " !pip install unsloth\n", + "else:\n", + " # Do this only in Colab notebooks! Otherwise use pip install unsloth\n", + " import torch; v = re.match(r\"[0-9\\.]{3,}\", str(torch.__version__)).group(0)\n", + " xformers = \"xformers==\" + (\"0.0.32.post2\" if v == \"2.8.0\" else \"0.0.29.post3\")\n", + " !pip install --no-deps bitsandbytes accelerate {xformers} peft trl triton cut_cross_entropy unsloth_zoo\n", + " !pip install sentencepiece protobuf \"datasets>=3.4.1,<4.0.0\" \"huggingface_hub>=0.34.0\" hf_transfer\n", + " !pip install --no-deps unsloth\n", + "!pip install transformers==4.56.2\n", + "!pip install --no-deps trl==0.22.2\n", + "import torch; torch._dynamo.config.recompile_limit = 64;\n" + ] }, { "cell_type": "code", @@ -111,8 +126,8 @@ "name": "stdout", "output_type": "stream", "text": [ - "\ud83e\udda5 Unsloth: Will patch your computer to enable 2x faster free finetuning.\n", - "\ud83e\udda5 Unsloth Zoo will now patch everything to make training faster!\n", + "🦥 Unsloth: Will patch your computer to enable 2x faster free finetuning.\n", + "🦥 Unsloth Zoo will now patch everything to make training faster!\n", "==((====))== Unsloth 2025.7.5: Fast Gemma3N patching. Transformers: 4.54.0.dev0.\n", " \\\\ /| Tesla T4. Num GPUs = 1. Max memory: 14.741 GB. Platform: Linux.\n", "O^O/ \\_/ \\ Torch: 2.6.0+cu124. CUDA: 7.5. CUDA Toolkit: 12.4. Triton: 3.2.0\n", @@ -269,7 +284,7 @@ "name": "stdout", "output_type": "stream", "text": [ - " Ich, ich rechne direkt mich an. Das ist nat\u00fcrlich klar, nur, dass, \u00e4h, es politische Interessen gibt im Handel, im Austausch mit Waren, dass es politische Einfl\u00fcsse gibt. Die Frage ist, die Alternative soll es nicht sein.\n" + " Ich, ich rechne direkt mich an. Das ist natürlich klar, nur, dass, äh, es politische Interessen gibt im Handel, im Austausch mit Waren, dass es politische Einflüsse gibt. Die Frage ist, die Alternative soll es nicht sein.\n" ] }, { @@ -320,7 +335,7 @@ "name": "stdout", "output_type": "stream", "text": [ - "Sie direkt mich an. Das finde ich klar, nur dass es politisch Interessen gibt im Handel, im Austausch mit Waren, dass es politische Einfl\u00fcsse gibt. Die Frage ist, die Alternative soll es nicht sein.\n" + "Sie direkt mich an. Das finde ich klar, nur dass es politisch Interessen gibt im Handel, im Austausch mit Waren, dass es politische Einflüsse gibt. Die Frage ist, die Alternative soll es nicht sein.\n" ] } ], @@ -1426,7 +1441,7 @@ "name": "stdout", "output_type": "stream", "text": [ - "Du sprichst direkt mich an. Das finde ich klar, nur, dass, \u00e4h, dass politische Interessen gibt im Handel, im Austausch mit Waren, dass es politische Einfl\u00fcsse gibt. Die Frage ist, die Alternative soll es nicht sein.\n" + "Du sprichst direkt mich an. Das finde ich klar, nur, dass, äh, dass politische Interessen gibt im Handel, im Austausch mit Waren, dass es politische Einflüsse gibt. Die Frage ist, die Alternative soll es nicht sein.\n" ] } ], @@ -1641,10 +1656,9 @@ "source": [ "if False: # Change to True to upload GGUF\n", " model.push_to_hub_gguf(\n", - " \"gemma-3N-finetune\",\n", + " \"HF_ACCOUNT/gemma-3N-finetune-gguf\",\n", " processor,\n", " quantization_method = \"Q8_0\", # Only Q8_0, BF16, F16 supported\n", - " repo_id = \"HF_ACCOUNT/gemma-3N-finetune-gguf\",\n", " token = \"hf_...\",\n", " )" ] @@ -1670,9 +1684,10 @@ " \n", " \n", "\n", - " Join Discord if you need help + \u2b50\ufe0f Star us on Github \u2b50\ufe0f\n", + " Join Discord if you need help + ⭐️ Star us on Github ⭐️\n", "\n", - "\n This notebook and all Unsloth notebooks are licensed [LGPL-3.0](https://github.com/unslothai/notebooks?tab=LGPL-3.0-1-ov-file#readme).\n" + "\n", + " This notebook and all Unsloth notebooks are licensed [LGPL-3.0](https://github.com/unslothai/notebooks?tab=LGPL-3.0-1-ov-file#readme).\n" ] } ], @@ -1793,9 +1808,9 @@ "description": "", "description_tooltip": null, "layout": "IPY_MODEL_dd596d7ce92847178805247ed2ea2902", - "placeholder": "\u200b", + "placeholder": "​", "style": "IPY_MODEL_56256ba8e73c48898b147d2b91f4fd85", - "value": "Loading\u2007checkpoint\u2007shards:\u2007100%" + "value": "Loading checkpoint shards: 100%" } }, "54cedbd8ef984f6a89590f1651804c03": { @@ -1881,9 +1896,9 @@ "description": "", "description_tooltip": null, "layout": "IPY_MODEL_9d544cff64354e6695e90cfd70743d72", - "placeholder": "\u200b", + "placeholder": "​", "style": "IPY_MODEL_3e16f926611b458fbfa21f75bd8de2c2", - "value": "Map\u2007(num_proc=4):\u2007100%" + "value": "Map (num_proc=4): 100%" } }, "6dbca67a4bcf491fa0cdc07f10cca9c2": { @@ -2352,9 +2367,9 @@ "description": "", "description_tooltip": null, "layout": "IPY_MODEL_2d0675287f864fbdac1ca1439bc50077", - "placeholder": "\u200b", + "placeholder": "​", "style": "IPY_MODEL_8ef02bdc9627427d83a6324cb59c445e", - "value": "\u20073/3\u2007[00:39<00:00,\u200711.72s/it]" + "value": " 3/3 [00:39<00:00, 11.72s/it]" } }, "ecbee91d79834a49ab0cb3e33522d8d2": { @@ -2389,9 +2404,9 @@ "description": "", "description_tooltip": null, "layout": "IPY_MODEL_54cedbd8ef984f6a89590f1651804c03", - "placeholder": "\u200b", + "placeholder": "​", "style": "IPY_MODEL_9fdf6d3312be4f51912561ae1cb5a893", - "value": "\u20073000/3000\u2007[09:19<00:00,\u2007\u20073.22\u2007examples/s]" + "value": " 3000/3000 [09:19<00:00,  3.22 examples/s]" } }, "state": {} @@ -2400,4 +2415,4 @@ }, "nbformat": 4, "nbformat_minor": 0 -} \ No newline at end of file +} diff --git a/nb/Gemma3N_(4B)-Conversational.ipynb b/nb/Gemma3N_(4B)-Conversational.ipynb index 65ba66e4..502fdced 100644 --- a/nb/Gemma3N_(4B)-Conversational.ipynb +++ b/nb/Gemma3N_(4B)-Conversational.ipynb @@ -8,7 +8,7 @@ "
\n", "\n", "\n", - " Join Discord if you need help + \u2b50 Star us on Github \u2b50\n", + " Join Discord if you need help + ⭐ Star us on Github ⭐\n", "
\n", "\n", "To install Unsloth your local device, follow [our guide](https://docs.unsloth.ai/get-started/install-and-update). This notebook is licensed [LGPL-3.0](https://github.com/unslothai/notebooks?tab=LGPL-3.0-1-ov-file#readme).\n", @@ -51,7 +51,22 @@ "execution_count": null, "metadata": {}, "outputs": [], - "source": "%%capture\nimport os, re\nif \"COLAB_\" not in \"\".join(os.environ.keys()):\n !pip install unsloth\nelse:\n # Do this only in Colab notebooks! Otherwise use pip install unsloth\n import torch; v = re.match(r\"[0-9\\.]{3,}\", str(torch.__version__)).group(0)\n xformers = \"xformers==\" + (\"0.0.32.post2\" if v == \"2.8.0\" else \"0.0.29.post3\")\n !pip install --no-deps bitsandbytes accelerate {xformers} peft trl triton cut_cross_entropy unsloth_zoo\n !pip install sentencepiece protobuf \"datasets>=3.4.1,<4.0.0\" \"huggingface_hub>=0.34.0\" hf_transfer\n !pip install --no-deps unsloth\n!pip install transformers==4.56.2\n!pip install --no-deps trl==0.22.2\nimport torch; torch._dynamo.config.recompile_limit = 64;\n" + "source": [ + "%%capture\n", + "import os, re\n", + "if \"COLAB_\" not in \"\".join(os.environ.keys()):\n", + " !pip install unsloth\n", + "else:\n", + " # Do this only in Colab notebooks! Otherwise use pip install unsloth\n", + " import torch; v = re.match(r\"[0-9\\.]{3,}\", str(torch.__version__)).group(0)\n", + " xformers = \"xformers==\" + (\"0.0.32.post2\" if v == \"2.8.0\" else \"0.0.29.post3\")\n", + " !pip install --no-deps bitsandbytes accelerate {xformers} peft trl triton cut_cross_entropy unsloth_zoo\n", + " !pip install sentencepiece protobuf \"datasets>=3.4.1,<4.0.0\" \"huggingface_hub>=0.34.0\" hf_transfer\n", + " !pip install --no-deps unsloth\n", + "!pip install transformers==4.56.2\n", + "!pip install --no-deps trl==0.22.2\n", + "import torch; torch._dynamo.config.recompile_limit = 64;\n" + ] }, { "cell_type": "code", @@ -237,8 +252,8 @@ "name": "stdout", "output_type": "stream", "text": [ - "\ud83e\udda5 Unsloth: Will patch your computer to enable 2x faster free finetuning.\n", - "\ud83e\udda5 Unsloth Zoo will now patch everything to make training faster!\n", + "🦥 Unsloth: Will patch your computer to enable 2x faster free finetuning.\n", + "🦥 Unsloth Zoo will now patch everything to make training faster!\n", "==((====))== Unsloth 2025.6.12: Fast Gemma3N patching. Transformers: 4.54.0.dev0.\n", " \\\\ /| Tesla T4. Num GPUs = 1. Max memory: 14.741 GB. Platform: Linux.\n", "O^O/ \\_/ \\ Torch: 2.6.0+cu124. CUDA: 7.5. CUDA Toolkit: 12.4. Triton: 3.2.0\n", @@ -2035,10 +2050,9 @@ "source": [ "if False: # Change to True to upload GGUF\n", " model.push_to_hub_gguf(\n", - " \"gemma-3N-finetune\",\n", + " \"HF_ACCOUNT/gemma-3N-finetune-gguf\",\n", " tokenizer,\n", " quantization_method = \"Q8_0\", # Only Q8_0, BF16, F16 supported\n", - " repo_id = \"HF_ACCOUNT/gemma-3N-finetune-gguf\",\n", " token = \"hf_...\",\n", " )" ] @@ -2064,9 +2078,10 @@ " \n", " \n", "\n", - " Join Discord if you need help + \u2b50\ufe0f Star us on Github \u2b50\ufe0f\n", + " Join Discord if you need help + ⭐️ Star us on Github ⭐️\n", "\n", - "\n This notebook and all Unsloth notebooks are licensed [LGPL-3.0](https://github.com/unslothai/notebooks?tab=LGPL-3.0-1-ov-file#readme).\n" + "\n", + " This notebook and all Unsloth notebooks are licensed [LGPL-3.0](https://github.com/unslothai/notebooks?tab=LGPL-3.0-1-ov-file#readme).\n" ] } ], @@ -2112,9 +2127,9 @@ "description": "", "description_tooltip": null, "layout": "IPY_MODEL_d66ecbc2c4664427bb85cb4a3ae629a4", - "placeholder": "\u200b", + "placeholder": "​", "style": "IPY_MODEL_b6586c2ddfcc47ecb9175058ec70f220", - "value": "model-00003-of-00003.safetensors:\u2007100%" + "value": "model-00003-of-00003.safetensors: 100%" } }, "00cb8fa0460a4136a0a8bf5e2153a76f": { @@ -2133,9 +2148,9 @@ "description": "", "description_tooltip": null, "layout": "IPY_MODEL_d7d67d83b522461290d1881e8c5b60ea", - "placeholder": "\u200b", + "placeholder": "​", "style": "IPY_MODEL_ab83d29573b84bc08dc0af8d1aec2e89", - "value": "\u2007210/210\u2007[00:00<00:00,\u200716.7kB/s]" + "value": " 210/210 [00:00<00:00, 16.7kB/s]" } }, "0206f33a5dcb4007971ff0b91d90c3e6": { @@ -2295,9 +2310,9 @@ "description": "", "description_tooltip": null, "layout": "IPY_MODEL_a26e8d8d74434037a2855b4205c5e16f", - "placeholder": "\u200b", + "placeholder": "​", "style": "IPY_MODEL_5b5b02f392ae487b8e228d136bf1bbf5", - "value": "\u2007100000/100000\u2007[00:02<00:00,\u200749816.60\u2007examples/s]" + "value": " 100000/100000 [00:02<00:00, 49816.60 examples/s]" } }, "06ad544485aa4baeb122c8349d852794": { @@ -2541,9 +2556,9 @@ "description": "", "description_tooltip": null, "layout": "IPY_MODEL_d25c40d318e24f7c832f4ebb9a884b9e", - "placeholder": "\u200b", + "placeholder": "​", "style": "IPY_MODEL_286de8ee29bd4c77a32446c2194777ef", - "value": "Map\u2007(num_proc=2):\u2007100%" + "value": "Map (num_proc=2): 100%" } }, "18003f900be14303bca6a501e03fce41": { @@ -2636,9 +2651,9 @@ "description": "", "description_tooltip": null, "layout": "IPY_MODEL_c0b79ef54987489d91ef01cdc19b3175", - "placeholder": "\u200b", + "placeholder": "​", "style": "IPY_MODEL_5e0ab0e8fc144d27bc5834dd16b20ef6", - "value": "\u20071.20M/?\u2007[00:00<00:00,\u200741.4MB/s]" + "value": " 1.20M/? [00:00<00:00, 41.4MB/s]" } }, "1ba27593feb449018b37cd4924d479a1": { @@ -2709,9 +2724,9 @@ "description": "", "description_tooltip": null, "layout": "IPY_MODEL_2062ecc4fca44ad58b8963e84f7f09e4", - "placeholder": "\u200b", + "placeholder": "​", "style": "IPY_MODEL_3e5bc0d900e6454ba7d1d6a30839fa01", - "value": "\u20073000/3000\u2007[00:01<00:00,\u20072140.29\u2007examples/s]" + "value": " 3000/3000 [00:01<00:00, 2140.29 examples/s]" } }, "1e1e0903f1df4972824e67373f176c05": { @@ -2888,9 +2903,9 @@ "description": "", "description_tooltip": null, "layout": "IPY_MODEL_88ab0ec7df484277b739480e9ed6ae43", - "placeholder": "\u200b", + "placeholder": "​", "style": "IPY_MODEL_11f3d888a42949dd884e897b424db91e", - "value": "tokenizer.json:\u2007100%" + "value": "tokenizer.json: 100%" } }, "202f306725a647b380c383aa0b5ece6e": { @@ -3171,9 +3186,9 @@ "description": "", "description_tooltip": null, "layout": "IPY_MODEL_f740d4720e47404fab6a302c70647d96", - "placeholder": "\u200b", + "placeholder": "​", "style": "IPY_MODEL_deb0fa3589ea456dae2034da0f3c8c07", - "value": "Unsloth:\u2007Standardizing\u2007formats\u2007(num_proc=2):\u2007100%" + "value": "Unsloth: Standardizing formats (num_proc=2): 100%" } }, "2e2f97f0db284c6ca68949f0b627b795": { @@ -3501,9 +3516,9 @@ "description": "", "description_tooltip": null, "layout": "IPY_MODEL_d148202b13274d99a055ddfb94680b64", - "placeholder": "\u200b", + "placeholder": "​", "style": "IPY_MODEL_c978550e41f1436bac7e5123855b1495", - "value": "\u20073000/3000\u2007[00:00<00:00,\u20073802.71\u2007examples/s]" + "value": " 3000/3000 [00:00<00:00, 3802.71 examples/s]" } }, "3ad1ddfb8c6f43e2909ab08b72d10ec2": { @@ -3522,9 +3537,9 @@ "description": "", "description_tooltip": null, "layout": "IPY_MODEL_c23a8bea7c93423b872f0a5a17c157b3", - "placeholder": "\u200b", + "placeholder": "​", "style": "IPY_MODEL_5474bc98d61f4c6895943cb44f423ebf", - "value": "\u20073.72G/3.72G\u2007[00:39<00:00,\u200780.2MB/s]" + "value": " 3.72G/3.72G [00:39<00:00, 80.2MB/s]" } }, "3b8cf2a785e14020b020284880f8b726": { @@ -3714,9 +3729,9 @@ "description": "", "description_tooltip": null, "layout": "IPY_MODEL_7f6fe07a34ff498b83c858a598663c50", - "placeholder": "\u200b", + "placeholder": "​", "style": "IPY_MODEL_7961267807694e3384974b8734ac8cfd", - "value": "Generating\u2007train\u2007split:\u2007100%" + "value": "Generating train split: 100%" } }, "40721bbaf61b4c8e8114142be433108b": { @@ -3861,9 +3876,9 @@ "description": "", "description_tooltip": null, "layout": "IPY_MODEL_a46ffff5a95c489ab77f538cc0a776d1", - "placeholder": "\u200b", + "placeholder": "​", "style": "IPY_MODEL_e15f8583441842d8b9bdc4de9b590950", - "value": "\u2007370k/?\u2007[00:00<00:00,\u200721.7MB/s]" + "value": " 370k/? [00:00<00:00, 21.7MB/s]" } }, "463b74158c514bd599c4d34b1d72e996": { @@ -3974,9 +3989,9 @@ "description": "", "description_tooltip": null, "layout": "IPY_MODEL_9292da388d2546c9b3fa6ac0e505df20", - "placeholder": "\u200b", + "placeholder": "​", "style": "IPY_MODEL_202f306725a647b380c383aa0b5ece6e", - "value": "\u20071.63k/?\u2007[00:00<00:00,\u2007125kB/s]" + "value": " 1.63k/? [00:00<00:00, 125kB/s]" } }, "48fa153e76e84a2891a406d381b25ad3": { @@ -4032,9 +4047,9 @@ "description": "", "description_tooltip": null, "layout": "IPY_MODEL_0206f33a5dcb4007971ff0b91d90c3e6", - "placeholder": "\u200b", + "placeholder": "​", "style": "IPY_MODEL_ad4068f23d5e466fa3020cc8b7ff7bd6", - "value": "model-00002-of-00003.safetensors:\u2007100%" + "value": "model-00002-of-00003.safetensors: 100%" } }, "4e99df46e6ef4c9e9b0b83f3e81c8ecb": { @@ -4053,9 +4068,9 @@ "description": "", "description_tooltip": null, "layout": "IPY_MODEL_a831cceb89eb476288082efa7b426a9e", - "placeholder": "\u200b", + "placeholder": "​", "style": "IPY_MODEL_1ecd97cc62fc404e81fbb29b3865f382", - "value": "\u2007777/777\u2007[00:00<00:00,\u200777.7kB/s]" + "value": " 777/777 [00:00<00:00, 77.7kB/s]" } }, "501c9d8673a9449dacf217b24912dfcf": { @@ -4074,9 +4089,9 @@ "description": "", "description_tooltip": null, "layout": "IPY_MODEL_f4ac75045a5247fa913c47271437a910", - 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"placeholder": "\u200b", + "placeholder": "​", "style": "IPY_MODEL_025111e631d441a698ee21eb9ff6b8cc", - "value": "model-00001-of-00003.safetensors:\u2007100%" + "value": "model-00001-of-00003.safetensors: 100%" } }, "deb0fa3589ea456dae2034da0f3c8c07": { @@ -8315,9 +8330,9 @@ "description": "", "description_tooltip": null, "layout": "IPY_MODEL_2e2f97f0db284c6ca68949f0b627b795", - "placeholder": "\u200b", + "placeholder": "​", "style": "IPY_MODEL_d13e712c163445da9cf352331c75efd5", - "value": "\u20073/3\u2007[00:41<00:00,\u200712.51s/it]" + "value": " 3/3 [00:41<00:00, 12.51s/it]" } }, "eacfcd95ef1c4b49a6ff8897b815efdd": { @@ -8440,9 +8455,9 @@ "description": "", "description_tooltip": null, "layout": "IPY_MODEL_eacfcd95ef1c4b49a6ff8897b815efdd", - "placeholder": "\u200b", + "placeholder": "​", "style": "IPY_MODEL_35289ddb889645dfbb6c1688d8622d38", - "value": "Map:\u2007100%" + "value": "Map: 100%" } }, "eed5c6058d934c1aa1b1e892ab25811c": { @@ -8931,9 +8946,9 @@ "description": "", "description_tooltip": null, "layout": "IPY_MODEL_a4f6fb7e33c1420198017d98076ae099", - "placeholder": "\u200b", + "placeholder": "​", "style": "IPY_MODEL_48fa153e76e84a2891a406d381b25ad3", - "value": "\u20074.70M/4.70M\u2007[00:00<00:00,\u20079.78MB/s]" + "value": " 4.70M/4.70M [00:00<00:00, 9.78MB/s]" } }, "state": {} @@ -8942,4 +8957,4 @@ }, "nbformat": 4, "nbformat_minor": 0 -} \ No newline at end of file +} diff --git a/nb/Gemma3_(1B)-GRPO.ipynb b/nb/Gemma3_(1B)-GRPO.ipynb index b798c157..0405b1c4 100644 --- a/nb/Gemma3_(1B)-GRPO.ipynb +++ b/nb/Gemma3_(1B)-GRPO.ipynb @@ -8,7 +8,7 @@ "
\n", "\n", "\n", - " Join Discord if you need help + \u2b50 Star us on Github \u2b50\n", + " Join Discord if you need help + ⭐ Star us on Github ⭐\n", "
\n", "\n", "To install Unsloth your local device, follow [our guide](https://docs.unsloth.ai/get-started/install-and-update). This notebook is licensed [LGPL-3.0](https://github.com/unslothai/notebooks?tab=LGPL-3.0-1-ov-file#readme).\n", @@ -51,14 +51,42 @@ "execution_count": null, "metadata": {}, "outputs": [], - "source": "%%capture\nimport os\nos.environ[\"UNSLOTH_VLLM_STANDBY\"] = \"1\" # [NEW] Extra 30% context lengths!\nif \"COLAB_\" not in \"\".join(os.environ.keys()):\n # If you're not in Colab, just use pip install or uv pip install\n !pip install unsloth vllm\nelse:\n pass # For Colab / Kaggle, we need extra instructions hidden below \\/" + "source": [ + "%%capture\n", + "import os\n", + "os.environ[\"UNSLOTH_VLLM_STANDBY\"] = \"1\" # [NEW] Extra 30% context lengths!\n", + "if \"COLAB_\" not in \"\".join(os.environ.keys()):\n", + " # If you're not in Colab, just use pip install or uv pip install\n", + " !pip install unsloth vllm\n", + "else:\n", + " pass # For Colab / Kaggle, we need extra instructions hidden below \\/" + ] }, { "cell_type": "code", "execution_count": null, "metadata": {}, "outputs": [], - "source": "#@title Colab Extra Install { display-mode: \"form\" }\n%%capture\nimport os\n!pip install --upgrade -qqq uv\nif \"COLAB_\" not in \"\".join(os.environ.keys()):\n # If you're not in Colab, just use pip install!\n !pip install unsloth vllm\nelse:\n try: import numpy, PIL; get_numpy = f\"numpy=={numpy.__version__}\"; get_pil = f\"pillow=={PIL.__version__}\"\n except: get_numpy = \"numpy\"; get_pil = \"pillow\"\n try: import subprocess; is_t4 = \"Tesla T4\" in str(subprocess.check_output([\"nvidia-smi\"]))\n except: is_t4 = False\n get_vllm, get_triton = (\"vllm==0.9.2\", \"triton==3.2.0\") if is_t4 else (\"vllm==0.10.2\", \"triton\")\n !uv pip install -qqq --upgrade \\\n unsloth {get_vllm} {get_numpy} {get_pil} torchvision bitsandbytes xformers\n !uv pip install -qqq {get_triton}\n!uv pip install transformers==4.56.2\n!uv pip install --no-deps trl==0.22.2" + "source": [ + "#@title Colab Extra Install { display-mode: \"form\" }\n", + "%%capture\n", + "import os\n", + "!pip install --upgrade -qqq uv\n", + "if \"COLAB_\" not in \"\".join(os.environ.keys()):\n", + " # If you're not in Colab, just use pip install!\n", + " !pip install unsloth vllm\n", + "else:\n", + " try: import numpy, PIL; get_numpy = f\"numpy=={numpy.__version__}\"; get_pil = f\"pillow=={PIL.__version__}\"\n", + " except: get_numpy = \"numpy\"; get_pil = \"pillow\"\n", + " try: import subprocess; is_t4 = \"Tesla T4\" in str(subprocess.check_output([\"nvidia-smi\"]))\n", + " except: is_t4 = False\n", + " get_vllm, get_triton = (\"vllm==0.9.2\", \"triton==3.2.0\") if is_t4 else (\"vllm==0.10.2\", \"triton\")\n", + " !uv pip install -qqq --upgrade \\\n", + " unsloth {get_vllm} {get_numpy} {get_pil} torchvision bitsandbytes xformers\n", + " !uv pip install -qqq {get_triton}\n", + "!uv pip install transformers==4.56.2\n", + "!uv pip install --no-deps trl==0.22.2" + ] }, { "cell_type": "markdown", @@ -173,8 +201,8 @@ "name": "stdout", "output_type": "stream", "text": [ - "\ud83e\udda5 Unsloth: Will patch your computer to enable 2x faster free finetuning.\n", - "\ud83e\udda5 Unsloth Zoo will now patch everything to make training faster!\n", + "🦥 Unsloth: Will patch your computer to enable 2x faster free finetuning.\n", + "🦥 Unsloth Zoo will now patch everything to make training faster!\n", "INFO 03-19 15:51:40 [__init__.py:256] Automatically detected platform cuda.\n", "==((====))== Unsloth 2025.3.17: Fast Gemma3 patching. Transformers: 4.50.0.dev0. vLLM: 0.8.0.\n", " \\\\ /| Tesla T4. Num GPUs = 1. Max memory: 14.741 GB. Platform: Linux.\n", @@ -1367,15 +1395,15 @@ "Loan amount: $480,000\n", "Interest rate: We need to assume an interest rate for this problem. Let's assume an annual interest rate of 6% (this is a common rate).\n", "Loan term: 20 years, so 20 * 12 = 240 months\n", - "We will use the loan payment formula: M = P [ i(1 + i)^n ] / [ (1 + i)^n \u2013 1]\n", + "We will use the loan payment formula: M = P [ i(1 + i)^n ] / [ (1 + i)^n – 1]\n", "where M is the monthly payment, P is the loan amount, i is the monthly interest rate, and n is the number of months.\n", "\n", "Monthly interest rate (i) = Annual interest rate / 12 = 0.06 / 12 = 0.005\n", "Number of months (n) = 240\n", "\n", - "M = 480000 [ 0.005(1 + 0.005)^240 ] / [ (1 + 0.005)^240 \u2013 1]\n", - "M = 480000 [ 0.005(1.005)^240 ] / [ (1.005)^240 \u2013 1]\n", - "M = 480000 [ 0.005 * 3.310853] / [ 3.310853 \u2013 1]\n", + "M = 480000 [ 0.005(1 + 0.005)^240 ] / [ (1 + 0.005)^240 – 1]\n", + "M = 480000 [ 0.005(1.005)^240 ] / [ (1.005)^240 – 1]\n", + "M = 480000 [ 0.005 * 3.310853] / [ 3.310853 – 1]\n", "M = 480000 [ 0.016554265] / [2.310853]\n", "M = 480000 * 0.00703658\n", "M = $331.54\n", @@ -1384,15 +1412,15 @@ "Loan amount: $120,000\n", "Interest rate: We still assume an annual interest rate of 6% (this is a common rate).\n", "Loan term: 20 years, so 20 * 12 = 240 months\n", - "We will use the loan payment formula: M = P [ i(1 + i)^n ] / [ (1 + i)^n \u2013 1]\n", + "We will use the loan payment formula: M = P [ i(1 + i)^n ] / [ (1 + i)^n – 1]\n", "where M is the monthly payment, P is the loan amount, i is the monthly interest rate, and n is the number of months.\n", "\n", "Monthly interest rate (i) = Annual interest rate / 12 = 0.06 / 12 = 0.005\n", "Number of months (n) = 240\n", "\n", - "M = 120000 [ 0.005(1 + 0.005)^240 ] / [ (1 + 0.005)^240 \u2013 1]\n", - "M = 120000 [ 0.005(1.005)^240 ] / [ (1.005)^240 \u2013 1]\n", - "M = 120000 [ 0.005 * 3.310853 ] / [ 3.310853 \u2013 1]\n", + "M = 120000 [ 0.005(1 + 0.005)^240 ] / [ (1 + 0.005)^240 – 1]\n", + "M = 120000 [ 0.005(1.005)^240 ] / [ (1.005)^240 – 1]\n", + "M = 120000 [ 0.005 * 3.310853 ] / [ 3.310853 – 1]\n", "M = 120000 [ 0.016554265] / [2.310853]\n", "M = 1200 \n", "Extracted:\n", @@ -1929,10 +1957,9 @@ "source": [ "if False: # Change to True to upload GGUF\n", " model.push_to_hub_gguf(\n", - " \"gemma-3-finetune\",\n", + " \"HF_ACCOUNT/gemma-finetune-gguf\",\n", " tokenizer,\n", " quantization_method = \"Q8_0\", # Only Q8_0, BF16, F16 supported\n", - " repo_id = \"HF_ACCOUNT/gemma-finetune-gguf\",\n", " token = \"hf_...\",\n", " )" ] @@ -1958,9 +1985,10 @@ " \n", " \n", "\n", - " Join Discord if you need help + \u2b50\ufe0f Star us on Github \u2b50\ufe0f\n", + " Join Discord if you need help + ⭐️ Star us on Github ⭐️\n", "\n", - "\n This notebook and all Unsloth notebooks are licensed [LGPL-3.0](https://github.com/unslothai/notebooks?tab=LGPL-3.0-1-ov-file#readme).\n" + "\n", + " This notebook and all Unsloth notebooks are licensed [LGPL-3.0](https://github.com/unslothai/notebooks?tab=LGPL-3.0-1-ov-file#readme).\n" ] } ], @@ -2238,9 +2266,9 @@ "description": "", "description_tooltip": null, "layout": "IPY_MODEL_551b94fe4b3c4a4f8f3220d013a6d897", - "placeholder": "\u200b", + "placeholder": "​", "style": "IPY_MODEL_29d36346bc75470eacd30aebf1423e14", - "value": "tokenizer.json:\u2007100%" + "value": "tokenizer.json: 100%" } }, "0ef32700424c4799b8216de4ed8bbbb9": { @@ -2350,9 +2378,9 @@ "description": "", "description_tooltip": null, "layout": "IPY_MODEL_383d2f04eccd4e38ad791494a06423ed", - "placeholder": "\u200b", + "placeholder": "​", "style": "IPY_MODEL_36cabdee7cd645a58e1ffc794674a322", - "value": "special_tokens_map.json:\u2007100%" + "value": "special_tokens_map.json: 100%" } }, "1664b23faa1b4292bb5727bd525c45be": { @@ -2445,9 +2473,9 @@ "description": "", "description_tooltip": null, "layout": "IPY_MODEL_772360d1551141c5ab0a877ae4ed1c76", - "placeholder": "\u200b", + "placeholder": "​", "style": "IPY_MODEL_b0c51c819fff44c5a6e8e626fec9e937", - "value": "tokenizer_config.json:\u2007100%" + "value": "tokenizer_config.json: 100%" } }, "19731cf654e64eb3905f02f4ae277e8c": { @@ -2842,9 +2870,9 @@ "description": "", "description_tooltip": null, "layout": "IPY_MODEL_6decae16dd5b404ba272d89df9c1372b", - "placeholder": "\u200b", + "placeholder": "​", "style": "IPY_MODEL_9151ae8e05634cf4a8ce42677f211bac", - "value": "Map:\u2007100%" + "value": "Map: 100%" } }, "340c07f1b7b14527a378880f9166ef55": { @@ -3000,9 +3028,9 @@ "description": "", "description_tooltip": null, "layout": "IPY_MODEL_671b4725f18a4c809b3c97a65ec9e405", - "placeholder": "\u200b", + "placeholder": "​", "style": "IPY_MODEL_faa61469d4bc46aebe74d5401d42c3ab", - "value": "\u200735.0/35.0\u2007[00:00<00:00,\u20072.66kB/s]" + "value": " 35.0/35.0 [00:00<00:00, 2.66kB/s]" } }, "3fabb349d1f943b09ed25784a0d0ab0a": { @@ -3325,9 +3353,9 @@ "description": "", "description_tooltip": null, "layout": "IPY_MODEL_cf83a6e558f64ff98276981a82f3b2ac", - "placeholder": "\u200b", + "placeholder": "​", "style": "IPY_MODEL_0ef32700424c4799b8216de4ed8bbbb9", - "value": "test-00000-of-00001.parquet:\u2007100%" + "value": "test-00000-of-00001.parquet: 100%" } }, "50503005b58845b79254f89f95fb03d9": { @@ -3370,9 +3398,9 @@ "description": "", "description_tooltip": null, "layout": "IPY_MODEL_d1e38bbf7593462bb87b14bacee9e3d9", - "placeholder": "\u200b", + "placeholder": "​", "style": "IPY_MODEL_846c1dd9b3214c68bbfc362166a6b9ee", - "value": "\u20077473/7473\u2007[00:00<00:00,\u20075203.68\u2007examples/s]" + "value": " 7473/7473 [00:00<00:00, 5203.68 examples/s]" } }, "54c603df4e174b70bd03bce59de287b2": { @@ -3483,9 +3511,9 @@ "description": "", "description_tooltip": null, "layout": "IPY_MODEL_9677dc2a2f4847d89d3ca42c01435205", - "placeholder": "\u200b", + "placeholder": "​", "style": "IPY_MODEL_645b707de96a4c2eb07eb118db311fb6", - "value": "Generating\u2007train\u2007split:\u2007100%" + "value": "Generating train split: 100%" } }, "61d7ca5d56f14d7d93d5cf5e5b712da2": { @@ -4032,9 +4060,9 @@ "description": "", "description_tooltip": null, "layout": "IPY_MODEL_669cb00554134e8287d0daae7372d397", - "placeholder": "\u200b", + "placeholder": "​", "style": "IPY_MODEL_9e7bb56731134d9cba89cbde208358e0", - "value": "train-00000-of-00001.parquet:\u2007100%" + "value": "train-00000-of-00001.parquet: 100%" } }, "7c4cd321445b43bfa818b599d42c8cb7": { @@ -4053,9 +4081,9 @@ "description": "", "description_tooltip": null, "layout": "IPY_MODEL_cec948b41ee348fcbdf2f5fa290ffe42", - "placeholder": "\u200b", + "placeholder": "​", "style": "IPY_MODEL_6d1b19657db94907b6fdf0a3b3a05e84", - "value": "README.md:\u2007100%" + "value": "README.md: 100%" } }, "7d4b49f0c54046a89039d25ee7c11f6f": { @@ -4230,9 +4258,9 @@ "description": "", "description_tooltip": null, "layout": "IPY_MODEL_1da84b32592d432fb1a57358ddcdceff", - "placeholder": "\u200b", + "placeholder": "​", "style": "IPY_MODEL_bbcd20b75ce445bea7be9597efa68d73", - "value": "\u200733.4M/33.4M\u2007[00:00<00:00,\u2007144MB/s]" + "value": " 33.4M/33.4M [00:00<00:00, 144MB/s]" } }, "8464d2f310b045808bcd7206aa7c8cc5": { @@ -4281,9 +4309,9 @@ "description": "", "description_tooltip": null, "layout": "IPY_MODEL_70a0b21c05e642e5891bb8b91cfb2217", - "placeholder": "\u200b", + "placeholder": "​", "style": "IPY_MODEL_444aa81458bf4790915c188069506864", - "value": "tokenizer.model:\u2007100%" + "value": "tokenizer.model: 100%" } }, "859b75a69281413383fc1c0946bf63d0": { @@ -4333,9 +4361,9 @@ "description": "", "description_tooltip": null, "layout": "IPY_MODEL_02d6b8e9a02b470a92f700d9e7fea5d4", - "placeholder": "\u200b", + "placeholder": "​", "style": "IPY_MODEL_8464d2f310b045808bcd7206aa7c8cc5", - "value": "Generating\u2007test\u2007split:\u2007100%" + "value": "Generating test split: 100%" } }, "8a21cb24786049e2946c9a050a6673ab": { @@ -4406,9 +4434,9 @@ "description": "", "description_tooltip": null, "layout": "IPY_MODEL_0c96fa0b7ed344f4be44632451b406d7", - "placeholder": "\u200b", + "placeholder": "​", "style": "IPY_MODEL_bf96f070c2f54468a674f11681fcb22d", - "value": "\u20072.31M/2.31M\u2007[00:00<00:00,\u200717.7MB/s]" + "value": " 2.31M/2.31M [00:00<00:00, 17.7MB/s]" } }, "8ca7d620dc5d415a83b50f134317d925": { @@ -4800,9 +4828,9 @@ "description": "", "description_tooltip": null, "layout": "IPY_MODEL_67eda18557dc461483821ffd44a25eb4", - "placeholder": "\u200b", + "placeholder": "​", "style": "IPY_MODEL_4cabdb178b97464e875d507dd1410bbf", - "value": "\u20077.94k/7.94k\u2007[00:00<00:00,\u2007179kB/s]" + "value": " 7.94k/7.94k [00:00<00:00, 179kB/s]" } }, "9e7bb56731134d9cba89cbde208358e0": { @@ -5022,9 +5050,9 @@ "description": "", "description_tooltip": null, "layout": "IPY_MODEL_def9dbef26334436a6b2298b5b153f47", - "placeholder": "\u200b", + "placeholder": "​", "style": "IPY_MODEL_eea838fbfd2c4e82b1769fde1036487e", - "value": "\u20074.69M/4.69M\u2007[00:00<00:00,\u200726.2MB/s]" + "value": " 4.69M/4.69M [00:00<00:00, 26.2MB/s]" } }, "a9dbcb0e164544ba8321a7916500009d": { @@ -5199,9 +5227,9 @@ "description": "", "description_tooltip": null, "layout": "IPY_MODEL_45aa2714bf0b44e9af7668c674f63863", - "placeholder": "\u200b", + "placeholder": "​", "style": "IPY_MODEL_8ca7d620dc5d415a83b50f134317d925", - "value": "\u2007215/215\u2007[00:00<00:00,\u200713.4kB/s]" + "value": " 215/215 [00:00<00:00, 13.4kB/s]" } }, "b0c51c819fff44c5a6e8e626fec9e937": { @@ -5235,9 +5263,9 @@ "description": "", "description_tooltip": null, "layout": "IPY_MODEL_d9e72108a08b447ea2a29932391fe429", - "placeholder": "\u200b", + "placeholder": "​", "style": "IPY_MODEL_21366789f69d431bad2ac2c8d1ec1565", - "value": "\u20072.00G/2.00G\u2007[00:15<00:00,\u200771.2MB/s]" + "value": " 2.00G/2.00G [00:15<00:00, 71.2MB/s]" } }, "b67486cb78274f2baa4f9afdc2fd7e3c": { @@ -5256,9 +5284,9 @@ "description": "", "description_tooltip": null, "layout": "IPY_MODEL_21f2aec6d7af4c3a82306ad235674829", - "placeholder": "\u200b", + "placeholder": "​", "style": "IPY_MODEL_fd6ff32a3aa7479e8b5d0cda47819742", - "value": "model.safetensors:\u2007100%" + "value": "model.safetensors: 100%" } }, "ba4ac2596dda42698ae048f9b7a11c61": { @@ -5837,9 +5865,9 @@ "description": "", "description_tooltip": null, "layout": "IPY_MODEL_8029855dfa614963a7f5ff11d48dcbdb", - "placeholder": "\u200b", + "placeholder": "​", "style": "IPY_MODEL_e74fcfb683074f27806b6aaae329b74d", - "value": "\u2007670/670\u2007[00:00<00:00,\u200774.3kB/s]" + "value": " 670/670 [00:00<00:00, 74.3kB/s]" } }, "d7b48dafe15947c9b225681c4a326581": { @@ -5947,9 +5975,9 @@ "description": "", "description_tooltip": null, "layout": "IPY_MODEL_a9dbcb0e164544ba8321a7916500009d", - "placeholder": "\u200b", + "placeholder": "​", "style": "IPY_MODEL_a6030d7b5bbd460fb5aa1356c607ec82", - "value": "\u2007419k/419k\u2007[00:00<00:00,\u20079.62MB/s]" + "value": " 419k/419k [00:00<00:00, 9.62MB/s]" } }, "def9dbef26334436a6b2298b5b153f47": { @@ -6087,9 +6115,9 @@ "description": "", "description_tooltip": null, "layout": "IPY_MODEL_25c7874a020344e7aad2869f7a27db4e", - "placeholder": "\u200b", + "placeholder": "​", "style": "IPY_MODEL_86e9660b2d72460c836d9bba348be56b", - "value": "\u20071319/1319\u2007[00:00<00:00,\u200712220.76\u2007examples/s]" + "value": " 1319/1319 [00:00<00:00, 12220.76 examples/s]" } }, "ed53e921682348b28e2be40eaf96cbf7": { @@ -6132,9 +6160,9 @@ "description": "", "description_tooltip": null, "layout": "IPY_MODEL_185b378797334c819f8a199760cac945", - "placeholder": "\u200b", + "placeholder": "​", "style": "IPY_MODEL_a1fced067e1e40cbb08e25c9377123e0", - "value": "generation_config.json:\u2007100%" + "value": "generation_config.json: 100%" } }, "eea838fbfd2c4e82b1769fde1036487e": { @@ -6168,9 +6196,9 @@ "description": "", "description_tooltip": null, "layout": "IPY_MODEL_45eda31f22294728bbca360abad799e6", - "placeholder": "\u200b", + "placeholder": "​", "style": "IPY_MODEL_d7b48dafe15947c9b225681c4a326581", - "value": "\u20071.16M/1.16M\u2007[00:00<00:00,\u20076.41MB/s]" + "value": " 1.16M/1.16M [00:00<00:00, 6.41MB/s]" } }, "efaa563da24149aaaa153b7e8c473394": { @@ -6348,9 +6376,9 @@ "description": "", "description_tooltip": null, "layout": "IPY_MODEL_aaf739645f654cd6a94d897358b2c2e0", - "placeholder": "\u200b", + "placeholder": "​", "style": "IPY_MODEL_f0c1afb62d8a4616a8df27c9de866916", - "value": "added_tokens.json:\u2007100%" + "value": "added_tokens.json: 100%" } }, "f6a520e1570d4f7faffc1b6e2c6200d2": { @@ -6369,9 +6397,9 @@ "description": "", "description_tooltip": null, "layout": "IPY_MODEL_10c20527dc19466eb4d6eb325529a0df", - "placeholder": "\u200b", + "placeholder": "​", "style": "IPY_MODEL_8f2974213b954318902d39a1fda9b3fb", - "value": "\u20077473/7473\u2007[00:00<00:00,\u20079263.20\u2007examples/s]" + "value": " 7473/7473 [00:00<00:00, 9263.20 examples/s]" } }, "f73516b2403f411d925618cfa2af5f46": { @@ -6434,4 +6462,4 @@ }, "nbformat": 4, "nbformat_minor": 0 -} \ No newline at end of file +} diff --git a/nb/Gemma3_(270M).ipynb b/nb/Gemma3_(270M).ipynb index 1573e2fa..1f91eac1 100644 --- a/nb/Gemma3_(270M).ipynb +++ b/nb/Gemma3_(270M).ipynb @@ -8,7 +8,7 @@ "
\n", "\n", "\n", - " Join Discord if you need help + \u2b50 Star us on Github \u2b50\n", + " Join Discord if you need help + ⭐ Star us on Github ⭐\n", "
\n", "\n", "To install Unsloth your local device, follow [our guide](https://docs.unsloth.ai/get-started/install-and-update). This notebook is licensed [LGPL-3.0](https://github.com/unslothai/notebooks?tab=LGPL-3.0-1-ov-file#readme).\n", @@ -51,7 +51,21 @@ "execution_count": null, "metadata": {}, "outputs": [], - "source": "%%capture\nimport os, re\nif \"COLAB_\" not in \"\".join(os.environ.keys()):\n !pip install unsloth\nelse:\n # Do this only in Colab notebooks! Otherwise use pip install unsloth\n import torch; v = re.match(r\"[0-9\\.]{3,}\", str(torch.__version__)).group(0)\n xformers = \"xformers==\" + (\"0.0.32.post2\" if v == \"2.8.0\" else \"0.0.29.post3\")\n !pip install --no-deps bitsandbytes accelerate {xformers} peft trl triton cut_cross_entropy unsloth_zoo\n !pip install sentencepiece protobuf \"datasets>=3.4.1,<4.0.0\" \"huggingface_hub>=0.34.0\" hf_transfer\n !pip install --no-deps unsloth\n!pip install transformers==4.56.2\n!pip install --no-deps trl==0.22.2" + "source": [ + "%%capture\n", + "import os, re\n", + "if \"COLAB_\" not in \"\".join(os.environ.keys()):\n", + " !pip install unsloth\n", + "else:\n", + " # Do this only in Colab notebooks! Otherwise use pip install unsloth\n", + " import torch; v = re.match(r\"[0-9\\.]{3,}\", str(torch.__version__)).group(0)\n", + " xformers = \"xformers==\" + (\"0.0.32.post2\" if v == \"2.8.0\" else \"0.0.29.post3\")\n", + " !pip install --no-deps bitsandbytes accelerate {xformers} peft trl triton cut_cross_entropy unsloth_zoo\n", + " !pip install sentencepiece protobuf \"datasets>=3.4.1,<4.0.0\" \"huggingface_hub>=0.34.0\" hf_transfer\n", + " !pip install --no-deps unsloth\n", + "!pip install transformers==4.56.2\n", + "!pip install --no-deps trl==0.22.2" + ] }, { "cell_type": "markdown", @@ -170,8 +184,8 @@ "name": "stdout", "output_type": "stream", "text": [ - "\ud83e\udda5 Unsloth: Will patch your computer to enable 2x faster free finetuning.\n", - "\ud83e\udda5 Unsloth Zoo will now patch everything to make training faster!\n", + "🦥 Unsloth: Will patch your computer to enable 2x faster free finetuning.\n", + "🦥 Unsloth Zoo will now patch everything to make training faster!\n", "==((====))== Unsloth 2025.8.9: Fast Gemma3 patching. Transformers: 4.55.2.\n", " \\\\ /| Tesla T4. Num GPUs = 1. Max memory: 14.741 GB. Platform: Linux.\n", "O^O/ \\_/ \\ Torch: 2.8.0+cu126. CUDA: 7.5. CUDA Toolkit: 12.6. Triton: 3.4.0\n", @@ -1723,7 +1737,7 @@ }, { "cell_type": "code", - "execution_count": 22, + "execution_count": null, "metadata": { "id": "S-TqCnZVu5Ll" }, @@ -1731,10 +1745,9 @@ "source": [ "if False: # Change to True to upload GGUF\n", " model.push_to_hub_gguf(\n", - " \"gemma-3-finetune\",\n", + " \"HF_ACCOUNT/gemma-finetune-gguf\",\n", " tokenizer,\n", " quantization_method = \"Q8_0\", # Only Q8_0, BF16, F16 supported\n", - " repo_id = \"HF_ACCOUNT/gemma-finetune-gguf\",\n", " token = \"hf_...\",\n", " )" ] @@ -1760,9 +1773,10 @@ " \n", " \n", "\n", - " Join Discord if you need help + \u2b50\ufe0f Star us on Github \u2b50\ufe0f\n", + " Join Discord if you need help + ⭐️ Star us on Github ⭐️\n", "\n", - "\n This notebook and all Unsloth notebooks are licensed [LGPL-3.0](https://github.com/unslothai/notebooks?tab=LGPL-3.0-1-ov-file#readme).\n" + "\n", + " This notebook and all Unsloth notebooks are licensed [LGPL-3.0](https://github.com/unslothai/notebooks?tab=LGPL-3.0-1-ov-file#readme).\n" ] } ], @@ -2128,9 +2142,9 @@ "description": "", "description_tooltip": null, "layout": "IPY_MODEL_e94421d86a43458897f4f66d91cd6989", - "placeholder": "\u200b", + "placeholder": "​", "style": "IPY_MODEL_9fc1e84815614dbfa5b6724343fd9739", - "value": "Map\u2007(num_proc=2):\u2007100%" + "value": "Map (num_proc=2): 100%" } }, "09e5f8c395244dafa7ac3c6334b47413": { @@ -2149,9 +2163,9 @@ "description": "", "description_tooltip": null, "layout": "IPY_MODEL_02befe13af4646afb239fab1f507ee4c", - "placeholder": "\u200b", + "placeholder": "​", "style": "IPY_MODEL_6469d5b42b0446d9ae18d2d5d81979cd", - "value": "model.safetensors:\u2007100%" + "value": "model.safetensors: 100%" } }, "09f74c4e1b9d47a4b5ede2a2bf0ee085": { @@ -2208,9 +2222,9 @@ "description": "", "description_tooltip": null, "layout": "IPY_MODEL_a31d15ba75bd40349f8f112500f27f5a", - "placeholder": "\u200b", + "placeholder": "​", "style": "IPY_MODEL_18cd442e5d18453a96ef40976d152b5b", - "value": "Unsloth:\u2007Tokenizing\u2007["text"]\u2007(num_proc=2):\u2007100%" + "value": "Unsloth: Tokenizing ["text"] (num_proc=2): 100%" } }, "0ad55edc028846aab73f324761d366c8": { @@ -2259,9 +2273,9 @@ "description": "", "description_tooltip": null, "layout": "IPY_MODEL_c3d22631abda42aeaa2f2bf75549711d", - 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"placeholder": "\u200b", + "placeholder": "​", "style": "IPY_MODEL_5bf5f53691394c3ab98c89e4eef4b126", - "value": "Generating\u2007train\u2007split:\u2007100%" + "value": "Generating train split: 100%" } }, "7b30129ea1434e51a3687be179f3970f": { @@ -4411,9 +4425,9 @@ "description": "", "description_tooltip": null, "layout": "IPY_MODEL_9fbe3d30ee1d4d7ca37a7a21393ca0cf", - "placeholder": "\u200b", + "placeholder": "​", "style": "IPY_MODEL_0ad55edc028846aab73f324761d366c8", - "value": "train.csv:\u2007100%" + "value": "train.csv: 100%" } }, "7f943bc4a0324512b8d4676a54478ca6": { @@ -5535,9 +5549,9 @@ "description": "", "description_tooltip": null, "layout": "IPY_MODEL_1869a88bc8a746deb688b7a167e0e435", - "placeholder": "\u200b", + "placeholder": "​", "style": "IPY_MODEL_e4bc0f9b79324981996cd8bb64999102", - "value": "\u2007670/670\u2007[00:00<00:00,\u200768.9kB/s]" + "value": " 670/670 [00:00<00:00, 68.9kB/s]" } }, "aa608bff07144ebd87db7c553dc0871c": { @@ -5595,9 +5609,9 @@ "description": "", "description_tooltip": null, "layout": "IPY_MODEL_079d7188aa2d40b1b2b456b03207f45f", - "placeholder": "\u200b", + "placeholder": "​", "style": "IPY_MODEL_b4d6bbe3e28e45f78a12d3b6894dbc8f", - "value": "Map:\u2007100%" + "value": "Map: 100%" } }, "ac689abda18c4505a2bab3d825520256": { @@ -5616,9 +5630,9 @@ "description": "", "description_tooltip": null, "layout": "IPY_MODEL_d70208bd6509427d8dea665b562afe97", - "placeholder": "\u200b", + "placeholder": "​", "style": "IPY_MODEL_0e2e7cdb95424275b64b5981101aec62", - "value": "tokenizer_config.json:\u2007" + "value": "tokenizer_config.json: " } }, "ad2af65570ac4f97a88cabb213eb7279": { @@ -5787,9 +5801,9 @@ "description": "", "description_tooltip": null, "layout": "IPY_MODEL_2e3acda027604864880f9f5468af440f", - "placeholder": "\u200b", + "placeholder": "​", "style": "IPY_MODEL_c3d6f918c93a4afabd5cd44faa0c5ab6", - "value": "\u20074.69M/4.69M\u2007[00:00<00:00,\u200710.4MB/s]" + "value": " 4.69M/4.69M [00:00<00:00, 10.4MB/s]" } }, "b4d6bbe3e28e45f78a12d3b6894dbc8f": { @@ -5860,9 +5874,9 @@ "description": "", "description_tooltip": null, "layout": "IPY_MODEL_a9cdb006e52f4fc9ae6419c5402003d0", - 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"placeholder": "\u200b", + "placeholder": "​", "style": "IPY_MODEL_e463361f8da04184b74c46026646603d", - "value": "\u200710000/10000\u2007[00:15<00:00,\u2007784.90\u2007examples/s]" + "value": " 10000/10000 [00:15<00:00, 784.90 examples/s]" } }, "cdd18433b8d34830acc931c17a7ffa20": { @@ -6436,9 +6450,9 @@ "description": "", "description_tooltip": null, "layout": "IPY_MODEL_bd0a44f558f44b50979b54d4ea798abf", - "placeholder": "\u200b", + "placeholder": "​", "style": "IPY_MODEL_d58b253b1998452c9d368bbb9e6d6874", - "value": "special_tokens_map.json:\u2007100%" + "value": "special_tokens_map.json: 100%" } }, "d0334d9a298e438f9fafff52c9fd1ff6": { @@ -6713,9 +6727,9 @@ "description": "", "description_tooltip": null, "layout": "IPY_MODEL_25553bbb43484be0999634a1e0e18476", - "placeholder": "\u200b", + "placeholder": "​", "style": "IPY_MODEL_a533946196404c53a75e5662492cd104", - "value": "Map:\u2007100%" + "value": "Map: 100%" } }, "dece51c7055a40a4abd1972e903b2daa": { @@ -6786,9 +6800,9 @@ "description": "", "description_tooltip": null, "layout": "IPY_MODEL_3c9701cf1030446aa05faaaf7bf9c3b8", - "placeholder": "\u200b", + "placeholder": "​", "style": "IPY_MODEL_c5138810c87b459e99eace35d6a9986d", - "value": "\u200799000/99000\u2007[00:03<00:00,\u200734705.61\u2007examples/s]" + "value": " 99000/99000 [00:03<00:00, 34705.61 examples/s]" } }, "e2e1ca627a8f4ca39aa2d50fb71b177b": { @@ -6807,9 +6821,9 @@ "description": "", "description_tooltip": null, "layout": "IPY_MODEL_5839f1581d6d46b4a0c48355271f3185", - "placeholder": "\u200b", + "placeholder": "​", "style": "IPY_MODEL_8e2b78001ccc4322b8ddfd04f32bdcc4", - "value": "\u20072.93k/?\u2007[00:00<00:00,\u2007128kB/s]" + "value": " 2.93k/? [00:00<00:00, 128kB/s]" } }, "e463361f8da04184b74c46026646603d": { @@ -7029,9 +7043,9 @@ "description": "", "description_tooltip": null, "layout": "IPY_MODEL_dece51c7055a40a4abd1972e903b2daa", - "placeholder": "\u200b", + "placeholder": "​", "style": "IPY_MODEL_59b145566f504bc09e5523310ed24638", - "value": "\u200710000/10000\u2007[00:26<00:00,\u2007507.96\u2007examples/s]" + "value": " 10000/10000 [00:26<00:00, 507.96 examples/s]" } }, "eb6e9f62a4684b9eabc046e97f7a5832": { @@ -7050,9 +7064,9 @@ "description": "", "description_tooltip": null, "layout": "IPY_MODEL_89c64bc929cb48e59c56279123dab92f", - "placeholder": "\u200b", + "placeholder": "​", "style": "IPY_MODEL_408a44c1d37d49b6a51bd454d21b5787", - "value": "\u20071.65k/?\u2007[00:00<00:00,\u2007154kB/s]" + "value": " 1.65k/? [00:00<00:00, 154kB/s]" } }, "ec6efb7a3da54ce5a5602d47e76c629e": { @@ -7279,9 +7293,9 @@ "description": "", "description_tooltip": null, "layout": "IPY_MODEL_fa00c7889ecd45dda1e59840a72bb322", - "placeholder": "\u200b", + "placeholder": "​", "style": "IPY_MODEL_5163464d76784dcb95432f8642e24fd7", - "value": "\u20071000/1000\u2007[00:00<00:00,\u20078986.31\u2007examples/s]" + "value": " 1000/1000 [00:00<00:00, 8986.31 examples/s]" } }, "f1fa17d1302c44bc8eed101dcbd49875": { @@ -7316,9 +7330,9 @@ "description": "", "description_tooltip": null, "layout": "IPY_MODEL_dd16102294d14fec8288d8d7dda6d33e", - "placeholder": "\u200b", + "placeholder": "​", "style": "IPY_MODEL_5be7ed6061b84610a16b2d9c3504c234", - "value": "\u2007233/233\u2007[00:00<00:00,\u200714.9kB/s]" + "value": " 233/233 [00:00<00:00, 14.9kB/s]" } }, "f46a67499a2947dabe967152f3e314b6": { @@ -7337,9 +7351,9 @@ "description": "", "description_tooltip": null, "layout": "IPY_MODEL_13bc7213b9ec42cca68eccb169389778", - "placeholder": "\u200b", + "placeholder": "​", "style": "IPY_MODEL_afec33708ac1447abd9d163d33ea3fc2", - "value": "README.md:\u2007" + "value": "README.md: " } }, "f51ef90e456646b1be4437da9f1b8bd4": { @@ -7611,4 +7625,4 @@ }, "nbformat": 4, "nbformat_minor": 0 -} \ No newline at end of file +} diff --git a/nb/Gemma3_(27B)_A100-Conversational.ipynb b/nb/Gemma3_(27B)_A100-Conversational.ipynb index 3ed15b8d..6542a9a9 100644 --- a/nb/Gemma3_(27B)_A100-Conversational.ipynb +++ b/nb/Gemma3_(27B)_A100-Conversational.ipynb @@ -8,7 +8,7 @@ "
\n", "\n", "\n", - " Join Discord if you need help + \u2b50 Star us on Github \u2b50\n", + " Join Discord if you need help + ⭐ Star us on Github ⭐\n", "
\n", "\n", "To install Unsloth your local device, follow [our guide](https://docs.unsloth.ai/get-started/install-and-update). This notebook is licensed [LGPL-3.0](https://github.com/unslothai/notebooks?tab=LGPL-3.0-1-ov-file#readme).\n", @@ -51,7 +51,21 @@ "execution_count": null, "metadata": {}, "outputs": [], - "source": "%%capture\nimport os, re\nif \"COLAB_\" not in \"\".join(os.environ.keys()):\n !pip install unsloth\nelse:\n # Do this only in Colab notebooks! Otherwise use pip install unsloth\n import torch; v = re.match(r\"[0-9\\.]{3,}\", str(torch.__version__)).group(0)\n xformers = \"xformers==\" + (\"0.0.32.post2\" if v == \"2.8.0\" else \"0.0.29.post3\")\n !pip install --no-deps bitsandbytes accelerate {xformers} peft trl triton cut_cross_entropy unsloth_zoo\n !pip install sentencepiece protobuf \"datasets>=3.4.1,<4.0.0\" \"huggingface_hub>=0.34.0\" hf_transfer\n !pip install --no-deps unsloth\n!pip install transformers==4.56.2\n!pip install --no-deps trl==0.22.2" + "source": [ + "%%capture\n", + "import os, re\n", + "if \"COLAB_\" not in \"\".join(os.environ.keys()):\n", + " !pip install unsloth\n", + "else:\n", + " # Do this only in Colab notebooks! Otherwise use pip install unsloth\n", + " import torch; v = re.match(r\"[0-9\\.]{3,}\", str(torch.__version__)).group(0)\n", + " xformers = \"xformers==\" + (\"0.0.32.post2\" if v == \"2.8.0\" else \"0.0.29.post3\")\n", + " !pip install --no-deps bitsandbytes accelerate {xformers} peft trl triton cut_cross_entropy unsloth_zoo\n", + " !pip install sentencepiece protobuf \"datasets>=3.4.1,<4.0.0\" \"huggingface_hub>=0.34.0\" hf_transfer\n", + " !pip install --no-deps unsloth\n", + "!pip install transformers==4.56.2\n", + "!pip install --no-deps trl==0.22.2" + ] }, { "cell_type": "markdown", @@ -93,8 +107,8 @@ "name": "stdout", "output_type": "stream", "text": [ - "\ud83e\udda5 Unsloth: Will patch your computer to enable 2x faster free finetuning.\n", - "\ud83e\udda5 Unsloth Zoo will now patch everything to make training faster!\n", + "🦥 Unsloth: Will patch your computer to enable 2x faster free finetuning.\n", + "🦥 Unsloth Zoo will now patch everything to make training faster!\n", "==((====))== Unsloth 2025.9.1: Fast Gemma3 patching. Transformers: 4.55.4.\n", " \\\\ /| NVIDIA A100-SXM4-40GB. Num GPUs = 1. Max memory: 39.557 GB. Platform: Linux.\n", "O^O/ \\_/ \\ Torch: 2.8.0+cu126. CUDA: 8.0. CUDA Toolkit: 12.6. Triton: 3.4.0\n", @@ -1080,10 +1094,9 @@ "source": [ "if False: # Change to True to upload GGUF\n", " model.push_to_hub_gguf(\n", - " \"gemma-3-finetune\",\n", + " \"HF_ACCOUNT/gemma-finetune-gguf\",\n", " tokenizer,\n", " quantization_method = \"Q8_0\", # Only Q8_0, BF16, F16 supported\n", - " repo_id = \"HF_ACCOUNT/gemma-finetune-gguf\",\n", " token = \"hf_...\",\n", " )" ] @@ -1105,7 +1118,7 @@ " \n", " \n", "\n", - " Join Discord if you need help + \u2b50\ufe0f Star us on Github \u2b50\ufe0f\n", + " Join Discord if you need help + ⭐️ Star us on Github ⭐️\n", "\n", " This notebook and all Unsloth notebooks are licensed [LGPL-3.0](https://github.com/unslothai/notebooks?tab=LGPL-3.0-1-ov-file#readme)\n", "\n" @@ -1256,9 +1269,9 @@ "description": "", "description_tooltip": null, "layout": "IPY_MODEL_3ce1a50e1d624f4d9e679f148b4b31c7", - "placeholder": "\u200b", + "placeholder": "​", "style": "IPY_MODEL_ecd5db31b0604c09b7a86c5d578b3580", - "value": "\u20075/5\u2007[00:07<00:00,\u2007\u20071.17s/it]" + "value": " 5/5 [00:07<00:00,  1.17s/it]" } }, "3ce1a50e1d624f4d9e679f148b4b31c7": { @@ -1390,9 +1403,9 @@ "description": "", "description_tooltip": null, "layout": "IPY_MODEL_d2af8a2712bb42ab860ebda80da376bc", - "placeholder": "\u200b", + "placeholder": "​", "style": "IPY_MODEL_8524552679b94102b623aa616bbb9a02", - "value": "Loading\u2007checkpoint\u2007shards:\u2007100%" + "value": "Loading checkpoint shards: 100%" } }, "a254522d6e95440ea53f217785d98a4d": { @@ -1484,4 +1497,4 @@ }, "nbformat": 4, "nbformat_minor": 0 -} \ No newline at end of file +} diff --git a/nb/Gemma3_(4B).ipynb b/nb/Gemma3_(4B).ipynb index f0a41bc5..926ac253 100644 --- a/nb/Gemma3_(4B).ipynb +++ b/nb/Gemma3_(4B).ipynb @@ -8,7 +8,7 @@ "
\n", "\n", "\n", - " Join Discord if you need help + \u2b50 Star us on Github \u2b50\n", + " Join Discord if you need help + ⭐ Star us on Github ⭐\n", "
\n", "\n", "To install Unsloth your local device, follow [our guide](https://docs.unsloth.ai/get-started/install-and-update). This notebook is licensed [LGPL-3.0](https://github.com/unslothai/notebooks?tab=LGPL-3.0-1-ov-file#readme).\n", @@ -51,7 +51,21 @@ "execution_count": null, "metadata": {}, "outputs": [], - "source": "%%capture\nimport os, re\nif \"COLAB_\" not in \"\".join(os.environ.keys()):\n !pip install unsloth\nelse:\n # Do this only in Colab notebooks! Otherwise use pip install unsloth\n import torch; v = re.match(r\"[0-9\\.]{3,}\", str(torch.__version__)).group(0)\n xformers = \"xformers==\" + (\"0.0.32.post2\" if v == \"2.8.0\" else \"0.0.29.post3\")\n !pip install --no-deps bitsandbytes accelerate {xformers} peft trl triton cut_cross_entropy unsloth_zoo\n !pip install sentencepiece protobuf \"datasets>=3.4.1,<4.0.0\" \"huggingface_hub>=0.34.0\" hf_transfer\n !pip install --no-deps unsloth\n!pip install transformers==4.56.2\n!pip install --no-deps trl==0.22.2" + "source": [ + "%%capture\n", + "import os, re\n", + "if \"COLAB_\" not in \"\".join(os.environ.keys()):\n", + " !pip install unsloth\n", + "else:\n", + " # Do this only in Colab notebooks! Otherwise use pip install unsloth\n", + " import torch; v = re.match(r\"[0-9\\.]{3,}\", str(torch.__version__)).group(0)\n", + " xformers = \"xformers==\" + (\"0.0.32.post2\" if v == \"2.8.0\" else \"0.0.29.post3\")\n", + " !pip install --no-deps bitsandbytes accelerate {xformers} peft trl triton cut_cross_entropy unsloth_zoo\n", + " !pip install sentencepiece protobuf \"datasets>=3.4.1,<4.0.0\" \"huggingface_hub>=0.34.0\" hf_transfer\n", + " !pip install --no-deps unsloth\n", + "!pip install transformers==4.56.2\n", + "!pip install --no-deps trl==0.22.2" + ] }, { "cell_type": "markdown", @@ -192,9 +206,9 @@ "name": "stdout", "output_type": "stream", "text": [ - "\ud83e\udda5 Unsloth: Will patch your computer to enable 2x faster free finetuning.\n", + "🦥 Unsloth: Will patch your computer to enable 2x faster free finetuning.\n", "Unsloth: Successfully patched SmolVLMForConditionalGeneration for better torch.compile compatibility.\n", - "\ud83e\udda5 Unsloth Zoo will now patch everything to make training faster!\n", + "🦥 Unsloth Zoo will now patch everything to make training faster!\n", "==((====))== Unsloth 2025.3.19: Fast Gemma3 patching. Transformers: 4.50.2.\n", " \\\\ /| NVIDIA GeForce RTX 3060. Num GPUs = 1. Max memory: 11.755 GB. Platform: Linux.\n", "O^O/ \\_/ \\ Torch: 2.6.0+cu124. CUDA: 8.6. CUDA Toolkit: 12.4. Triton: 3.2.0\n", @@ -1308,10 +1322,9 @@ "source": [ "if False: # Change to True to upload GGUF\n", " model.push_to_hub_gguf(\n", - " \"gemma-3-finetune\",\n", + " \"HF_ACCOUNT/gemma-finetune-gguf\",\n", " tokenizer,\n", " quantization_method = \"Q8_0\", # Only Q8_0, BF16, F16 supported\n", - " repo_id = \"HF_ACCOUNT/gemma-finetune-gguf\",\n", " token = \"hf_...\",\n", " )" ] @@ -1335,9 +1348,10 @@ " \n", " \n", "\n", - " Join Discord if you need help + \u2b50\ufe0f Star us on Github \u2b50\ufe0f\n", + " Join Discord if you need help + ⭐️ Star us on Github ⭐️\n", "\n", - "\n This notebook and all Unsloth notebooks are licensed [LGPL-3.0](https://github.com/unslothai/notebooks?tab=LGPL-3.0-1-ov-file#readme).\n" + "\n", + " This notebook and all Unsloth notebooks are licensed [LGPL-3.0](https://github.com/unslothai/notebooks?tab=LGPL-3.0-1-ov-file#readme).\n" ] } ], @@ -1511,9 +1525,9 @@ "description": "", "description_tooltip": null, "layout": "IPY_MODEL_3530e2b431c041c6aeeaca4808ba0424", - 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"placeholder": "\u200b", + "placeholder": "​", "style": "IPY_MODEL_36c8135711194884be0e03cb5d3ae7e5", - "value": "\u20071.61k/1.61k\u2007[00:00<00:00,\u2007181kB/s]" + "value": " 1.61k/1.61k [00:00<00:00, 181kB/s]" } }, "0cba80b626574c11a44c6ce09b5d6e80": { @@ -1803,9 +1817,9 @@ "description": "", "description_tooltip": null, "layout": "IPY_MODEL_12d3049cca4a46c08cf5cdfcd5225248", - "placeholder": "\u200b", + "placeholder": "​", "style": "IPY_MODEL_6a9baf0a739c4790baf99b0ccadd6873", - "value": "\u200733.4M/33.4M\u2007[00:00<00:00,\u200770.2MB/s]" + "value": " 33.4M/33.4M [00:00<00:00, 70.2MB/s]" } }, "0db66084c58047aa84edf3b4fbede0c0": { @@ -1898,9 +1912,9 @@ "description": "", "description_tooltip": null, "layout": "IPY_MODEL_54d2fb7e7c2b4107ba758a7c7ef4f382", - "placeholder": "\u200b", + "placeholder": "​", "style": "IPY_MODEL_34da5010faa749e0940c2821f2f46e59", - "value": "\u2007100000/100000\u2007[00:43<00:00,\u20072627.58\u2007examples/s]" + "value": " 100000/100000 [00:43<00:00, 2627.58 examples/s]" } }, "173033e49f9f46d9930c6afddc983509": { @@ -1919,9 +1933,9 @@ "description": "", "description_tooltip": null, "layout": "IPY_MODEL_441ff92725ef40ce807daa1ff721faef", - "placeholder": "\u200b", + "placeholder": "​", "style": "IPY_MODEL_21136eec72034fcbb47a19f92aa0664d", - "value": "\u2007982/982\u2007[00:00<00:00,\u200778.7kB/s]" + "value": " 982/982 [00:00<00:00, 78.7kB/s]" } }, "17eaf723882e4efea38119978166fc75": { @@ -1940,9 +1954,9 @@ "description": "", "description_tooltip": null, "layout": "IPY_MODEL_cebd4fbf1fcf4ab2b65ecf539eda5a1e", - "placeholder": "\u200b", + "placeholder": "​", "style": "IPY_MODEL_f14ea72beac74152af5f970e634769ca", - "value": "generation_config.json:\u2007100%" + "value": "generation_config.json: 100%" } }, "18fce8679d7d4961b88bb2162e7aa9eb": { @@ -1961,9 +1975,9 @@ "description": "", "description_tooltip": null, "layout": "IPY_MODEL_f9439c3c9b3b4c4a84ed67aa0601a530", - "placeholder": "\u200b", + "placeholder": "​", "style": "IPY_MODEL_a89575b4c58348ac98566c22ab7e4118", - "value": "chat_template.json:\u2007100%" + "value": "chat_template.json: 100%" } }, "19c27988e01d47e79319f89b5cfd73e2": { @@ -2201,9 +2215,9 @@ "description": "", "description_tooltip": null, "layout": "IPY_MODEL_c5b1d1476ddc45249e037df07a96ae37", - "placeholder": "\u200b", + "placeholder": "​", "style": "IPY_MODEL_19c27988e01d47e79319f89b5cfd73e2", - "value": "Unsloth:\u2007Tokenizing\u2007["text"]\u2007(num_proc=2):\u2007100%" + "value": "Unsloth: Tokenizing ["text"] (num_proc=2): 100%" } }, "21136eec72034fcbb47a19f92aa0664d": { @@ -2237,9 +2251,9 @@ "description": "", "description_tooltip": null, "layout": "IPY_MODEL_9e20d704e64a4aaabe5e495c468d9670", - "placeholder": "\u200b", + "placeholder": "​", "style": "IPY_MODEL_ae4e4537ed1d4df4b1677700d190a2d2", - "value": "\u2007192/192\u2007[00:00<00:00,\u200720.1kB/s]" + "value": " 192/192 [00:00<00:00, 20.1kB/s]" } }, "28063728d31f45aea5beffd3f114eec7": { @@ -2599,9 +2613,9 @@ "description": "", "description_tooltip": null, "layout": "IPY_MODEL_9511c493311b4d4e94d5dc0aca4eeffb", - "placeholder": "\u200b", + "placeholder": "​", "style": "IPY_MODEL_f4265abad437426b8efa9091110c77c9", - "value": "train-00000-of-00001.parquet:\u2007100%" + "value": "train-00000-of-00001.parquet: 100%" } }, "34da5010faa749e0940c2821f2f46e59": { @@ -2791,9 +2805,9 @@ "description": "", "description_tooltip": null, "layout": "IPY_MODEL_70fdd31291b04dd68d66cf31c03d23ff", - "placeholder": "\u200b", + "placeholder": "​", "style": "IPY_MODEL_6feaf338d39440e78221649ac84af4a6", - "value": "special_tokens_map.json:\u2007100%" + "value": "special_tokens_map.json: 100%" } }, "36c8135711194884be0e03cb5d3ae7e5": { @@ -2905,9 +2919,9 @@ "description": "", "description_tooltip": null, "layout": "IPY_MODEL_7e5378838c114195ba3919fdd683fd7d", - "placeholder": "\u200b", + "placeholder": "​", "style": "IPY_MODEL_3350d22f463643ef9a726227f262ac49", - "value": "\u2007100000/100000\u2007[03:03<00:00,\u2007568.03\u2007examples/s]" + "value": " 100000/100000 [03:03<00:00, 568.03 examples/s]" } }, "409488926d2242c5a8e7b3d5b79c59db": { @@ -3213,9 +3227,9 @@ "description": "", "description_tooltip": null, "layout": "IPY_MODEL_5e9ba3247edc4fafa7687338424ddccb", - "placeholder": "\u200b", + "placeholder": "​", "style": "IPY_MODEL_97d7e3420e24436cb351b1e9679ff8b6", - "value": "\u2007670/670\u2007[00:00<00:00,\u200742.7kB/s]" + "value": " 670/670 [00:00<00:00, 42.7kB/s]" } }, "4e7cbb77617f43e6ae81e42eb7086fb7": { @@ -3428,9 +3442,9 @@ "description": "", "description_tooltip": null, "layout": "IPY_MODEL_52f091f99f0442f8bd14a50b7c870c1e", - "placeholder": "\u200b", + "placeholder": "​", "style": "IPY_MODEL_c859133fca324effb73ebc3520e746b6", - "value": "\u2007570/570\u2007[00:00<00:00,\u200761.1kB/s]" + "value": " 570/570 [00:00<00:00, 61.1kB/s]" } }, "55164fb3b49848beabfe0da534ab4b97": { @@ -3585,9 +3599,9 @@ "description": "", "description_tooltip": null, "layout": "IPY_MODEL_a15e4524521b42108f49dda23ed56023", - "placeholder": "\u200b", + "placeholder": "​", "style": "IPY_MODEL_a4eaae1b30d442208257c1870d549738", - "value": "processor_config.json:\u2007100%" + "value": "processor_config.json: 100%" } }, "5c01ab4767104c0c96c42858317f8877": { @@ -4212,9 +4226,9 @@ "description": "", "description_tooltip": null, "layout": "IPY_MODEL_73a283e64f324c27b38216e683050b92", - "placeholder": "\u200b", + "placeholder": "​", "style": "IPY_MODEL_81bddfaa180d4875b5cdb5cc4ae45dab", - "value": "added_tokens.json:\u2007100%" + "value": "added_tokens.json: 100%" } }, "77e843913b6e439ead9cf42725eedf3d": { @@ -4300,9 +4314,9 @@ "description": "", "description_tooltip": null, "layout": "IPY_MODEL_006e1f7432f84b298f61bb597b8aab10", - 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"placeholder": "\u200b", + "placeholder": "​", "style": "IPY_MODEL_bc6f29c9a1e14ce8be374867b8be86ac", - "value": "\u20071.16M/1.16M\u2007[00:00<00:00,\u200710.7MB/s]" + "value": " 1.16M/1.16M [00:00<00:00, 10.7MB/s]" } }, "dd6e4f9b4c6d4260a62b920a6812fd07": { @@ -6440,9 +6454,9 @@ "description": "", "description_tooltip": null, "layout": "IPY_MODEL_879c6a0498e54e5c87145c7f7d32de7e", - "placeholder": "\u200b", + "placeholder": "​", "style": "IPY_MODEL_740d351b7de241a6acabf6c2853585b6", - "value": "tokenizer.model:\u2007100%" + "value": "tokenizer.model: 100%" } }, "ded71beadafd438ebff07bb0594771e4": { @@ -6603,9 +6617,9 @@ "description": "", "description_tooltip": null, "layout": "IPY_MODEL_ce2ae7abaa4841478a732238269aa233", - "placeholder": "\u200b", + "placeholder": "​", "style": "IPY_MODEL_5fd55097dac149579c533b2798ebb442", - "value": "\u2007100000/100000\u2007[00:02<00:00,\u200760707.08\u2007examples/s]" + "value": " 100000/100000 [00:02<00:00, 60707.08 examples/s]" } }, "e12bca7d49b149b5b1124c28a669db98": { @@ -6700,9 +6714,9 @@ "description": "", "description_tooltip": null, "layout": "IPY_MODEL_490baae8c2294c2194f32dae183ce833", - 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"placeholder": "\u200b", + "placeholder": "​", "style": "IPY_MODEL_529996f48ccf404584725386d33401f9", - "value": "Map:\u2007100%" + "value": "Map: 100%" } }, "fab7a02d350946ae9563a05cfd04e22b": { @@ -7187,4 +7201,4 @@ }, "nbformat": 4, "nbformat_minor": 4 -} \ No newline at end of file +} diff --git a/nb/HuggingFace Course-Gemma3_(1B)-GRPO.ipynb b/nb/HuggingFace Course-Gemma3_(1B)-GRPO.ipynb index dc228c0d..7ea19cff 100644 --- a/nb/HuggingFace Course-Gemma3_(1B)-GRPO.ipynb +++ b/nb/HuggingFace Course-Gemma3_(1B)-GRPO.ipynb @@ -8,7 +8,7 @@ "
\n", "\n", "\n", - " Join Discord if you need help + \u2b50 Star us on Github \u2b50\n", + " Join Discord if you need help + ⭐ Star us on Github ⭐\n", "
\n", "\n", "In this [Hugging Face](https://huggingface.co/learn/nlp-course/en/chapter12/6?fw=pt) and Unsloth notebook, you will learn to transform Gemma3 (1B) GRPO into a Reasoning model using GRPO.\n", @@ -53,14 +53,42 @@ "execution_count": null, "metadata": {}, "outputs": [], - "source": "%%capture\nimport os\nos.environ[\"UNSLOTH_VLLM_STANDBY\"] = \"1\" # [NEW] Extra 30% context lengths!\nif \"COLAB_\" not in \"\".join(os.environ.keys()):\n # If you're not in Colab, just use pip install or uv pip install\n !pip install unsloth vllm\nelse:\n pass # For Colab / Kaggle, we need extra instructions hidden below \\/" + "source": [ + "%%capture\n", + "import os\n", + "os.environ[\"UNSLOTH_VLLM_STANDBY\"] = \"1\" # [NEW] Extra 30% context lengths!\n", + "if \"COLAB_\" not in \"\".join(os.environ.keys()):\n", + " # If you're not in Colab, just use pip install or uv pip install\n", + " !pip install unsloth vllm\n", + "else:\n", + " pass # For Colab / Kaggle, we need extra instructions hidden below \\/" + ] }, { "cell_type": "code", "execution_count": null, "metadata": {}, "outputs": [], - "source": "#@title Colab Extra Install { display-mode: \"form\" }\n%%capture\nimport os\n!pip install --upgrade -qqq uv\nif \"COLAB_\" not in \"\".join(os.environ.keys()):\n # If you're not in Colab, just use pip install!\n !pip install unsloth vllm\nelse:\n try: import numpy, PIL; get_numpy = f\"numpy=={numpy.__version__}\"; get_pil = f\"pillow=={PIL.__version__}\"\n except: get_numpy = \"numpy\"; get_pil = \"pillow\"\n try: import subprocess; is_t4 = \"Tesla T4\" in str(subprocess.check_output([\"nvidia-smi\"]))\n except: is_t4 = False\n get_vllm, get_triton = (\"vllm==0.9.2\", \"triton==3.2.0\") if is_t4 else (\"vllm==0.10.2\", \"triton\")\n !uv pip install -qqq --upgrade \\\n unsloth {get_vllm} {get_numpy} {get_pil} torchvision bitsandbytes xformers\n !uv pip install -qqq {get_triton}\n!uv pip install transformers==4.56.2\n!uv pip install --no-deps trl==0.22.2" + "source": [ + "#@title Colab Extra Install { display-mode: \"form\" }\n", + "%%capture\n", + "import os\n", + "!pip install --upgrade -qqq uv\n", + "if \"COLAB_\" not in \"\".join(os.environ.keys()):\n", + " # If you're not in Colab, just use pip install!\n", + " !pip install unsloth vllm\n", + "else:\n", + " try: import numpy, PIL; get_numpy = f\"numpy=={numpy.__version__}\"; get_pil = f\"pillow=={PIL.__version__}\"\n", + " except: get_numpy = \"numpy\"; get_pil = \"pillow\"\n", + " try: import subprocess; is_t4 = \"Tesla T4\" in str(subprocess.check_output([\"nvidia-smi\"]))\n", + " except: is_t4 = False\n", + " get_vllm, get_triton = (\"vllm==0.9.2\", \"triton==3.2.0\") if is_t4 else (\"vllm==0.10.2\", \"triton\")\n", + " !uv pip install -qqq --upgrade \\\n", + " unsloth {get_vllm} {get_numpy} {get_pil} torchvision bitsandbytes xformers\n", + " !uv pip install -qqq {get_triton}\n", + "!uv pip install transformers==4.56.2\n", + "!uv pip install --no-deps trl==0.22.2" + ] }, { "cell_type": "markdown", @@ -175,8 +203,8 @@ "name": "stdout", "output_type": "stream", "text": [ - "\ud83e\udda5 Unsloth: Will patch your computer to enable 2x faster free finetuning.\n", - "\ud83e\udda5 Unsloth Zoo will now patch everything to make training faster!\n", + "🦥 Unsloth: Will patch your computer to enable 2x faster free finetuning.\n", + "🦥 Unsloth Zoo will now patch everything to make training faster!\n", "INFO 03-19 15:51:40 [__init__.py:256] Automatically detected platform cuda.\n", "==((====))== Unsloth 2025.3.17: Fast Gemma3 patching. Transformers: 4.50.0.dev0. vLLM: 0.8.0.\n", " \\\\ /| Tesla T4. Num GPUs = 1. Max memory: 14.741 GB. Platform: Linux.\n", @@ -1369,15 +1397,15 @@ "Loan amount: $480,000\n", "Interest rate: We need to assume an interest rate for this problem. Let's assume an annual interest rate of 6% (this is a common rate).\n", "Loan term: 20 years, so 20 * 12 = 240 months\n", - "We will use the loan payment formula: M = P [ i(1 + i)^n ] / [ (1 + i)^n \u2013 1]\n", + "We will use the loan payment formula: M = P [ i(1 + i)^n ] / [ (1 + i)^n – 1]\n", "where M is the monthly payment, P is the loan amount, i is the monthly interest rate, and n is the number of months.\n", "\n", "Monthly interest rate (i) = Annual interest rate / 12 = 0.06 / 12 = 0.005\n", "Number of months (n) = 240\n", "\n", - "M = 480000 [ 0.005(1 + 0.005)^240 ] / [ (1 + 0.005)^240 \u2013 1]\n", - "M = 480000 [ 0.005(1.005)^240 ] / [ (1.005)^240 \u2013 1]\n", - "M = 480000 [ 0.005 * 3.310853] / [ 3.310853 \u2013 1]\n", + "M = 480000 [ 0.005(1 + 0.005)^240 ] / [ (1 + 0.005)^240 – 1]\n", + "M = 480000 [ 0.005(1.005)^240 ] / [ (1.005)^240 – 1]\n", + "M = 480000 [ 0.005 * 3.310853] / [ 3.310853 – 1]\n", "M = 480000 [ 0.016554265] / [2.310853]\n", "M = 480000 * 0.00703658\n", "M = $331.54\n", @@ -1386,15 +1414,15 @@ "Loan amount: $120,000\n", "Interest rate: We still assume an annual interest rate of 6% (this is a common rate).\n", "Loan term: 20 years, so 20 * 12 = 240 months\n", - "We will use the loan payment formula: M = P [ i(1 + i)^n ] / [ (1 + i)^n \u2013 1]\n", + "We will use the loan payment formula: M = P [ i(1 + i)^n ] / [ (1 + i)^n – 1]\n", "where M is the monthly payment, P is the loan amount, i is the monthly interest rate, and n is the number of months.\n", "\n", "Monthly interest rate (i) = Annual interest rate / 12 = 0.06 / 12 = 0.005\n", "Number of months (n) = 240\n", "\n", - "M = 120000 [ 0.005(1 + 0.005)^240 ] / [ (1 + 0.005)^240 \u2013 1]\n", - "M = 120000 [ 0.005(1.005)^240 ] / [ (1.005)^240 \u2013 1]\n", - "M = 120000 [ 0.005 * 3.310853 ] / [ 3.310853 \u2013 1]\n", + "M = 120000 [ 0.005(1 + 0.005)^240 ] / [ (1 + 0.005)^240 – 1]\n", + "M = 120000 [ 0.005(1.005)^240 ] / [ (1.005)^240 – 1]\n", + "M = 120000 [ 0.005 * 3.310853 ] / [ 3.310853 – 1]\n", "M = 120000 [ 0.016554265] / [2.310853]\n", "M = 1200 \n", "Extracted:\n", @@ -1931,10 +1959,9 @@ "source": [ "if False: # Change to True to upload GGUF\n", " model.push_to_hub_gguf(\n", - " \"gemma-3-finetune\",\n", + " \"HF_ACCOUNT/gemma-finetune-gguf\",\n", " tokenizer,\n", " quantization_method = \"Q8_0\", # Only Q8_0, BF16, F16 supported\n", - " repo_id = \"HF_ACCOUNT/gemma-finetune-gguf\",\n", " token = \"hf_...\",\n", " )" ] @@ -1960,9 +1987,10 @@ " \n", " \n", "\n", - " Join Discord if you need help + \u2b50\ufe0f Star us on Github \u2b50\ufe0f\n", + " Join Discord if you need help + ⭐️ Star us on Github ⭐️\n", "\n", - "\n This notebook and all Unsloth notebooks are licensed [LGPL-3.0](https://github.com/unslothai/notebooks?tab=LGPL-3.0-1-ov-file#readme).\n" + "\n", + " This notebook and all Unsloth notebooks are licensed [LGPL-3.0](https://github.com/unslothai/notebooks?tab=LGPL-3.0-1-ov-file#readme).\n" ] } ], @@ -2240,9 +2268,9 @@ "description": "", "description_tooltip": null, "layout": "IPY_MODEL_551b94fe4b3c4a4f8f3220d013a6d897", - "placeholder": "\u200b", + "placeholder": "​", "style": "IPY_MODEL_29d36346bc75470eacd30aebf1423e14", - "value": "tokenizer.json:\u2007100%" + "value": "tokenizer.json: 100%" } }, "0ef32700424c4799b8216de4ed8bbbb9": { @@ -2352,9 +2380,9 @@ "description": "", "description_tooltip": null, "layout": "IPY_MODEL_383d2f04eccd4e38ad791494a06423ed", - "placeholder": "\u200b", + "placeholder": "​", "style": "IPY_MODEL_36cabdee7cd645a58e1ffc794674a322", - "value": "special_tokens_map.json:\u2007100%" + "value": "special_tokens_map.json: 100%" } }, "1664b23faa1b4292bb5727bd525c45be": { @@ -2447,9 +2475,9 @@ "description": "", "description_tooltip": null, "layout": "IPY_MODEL_772360d1551141c5ab0a877ae4ed1c76", - "placeholder": "\u200b", + "placeholder": "​", "style": "IPY_MODEL_b0c51c819fff44c5a6e8e626fec9e937", - "value": "tokenizer_config.json:\u2007100%" + "value": "tokenizer_config.json: 100%" } }, "19731cf654e64eb3905f02f4ae277e8c": { @@ -2844,9 +2872,9 @@ "description": "", "description_tooltip": null, "layout": "IPY_MODEL_6decae16dd5b404ba272d89df9c1372b", - "placeholder": "\u200b", + "placeholder": "​", "style": "IPY_MODEL_9151ae8e05634cf4a8ce42677f211bac", - "value": "Map:\u2007100%" + "value": "Map: 100%" } }, "340c07f1b7b14527a378880f9166ef55": { @@ -3002,9 +3030,9 @@ "description": "", "description_tooltip": null, "layout": "IPY_MODEL_671b4725f18a4c809b3c97a65ec9e405", - 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"placeholder": "\u200b", + "placeholder": "​", "style": "IPY_MODEL_bbcd20b75ce445bea7be9597efa68d73", - "value": "\u200733.4M/33.4M\u2007[00:00<00:00,\u2007144MB/s]" + "value": " 33.4M/33.4M [00:00<00:00, 144MB/s]" } }, "8464d2f310b045808bcd7206aa7c8cc5": { @@ -4283,9 +4311,9 @@ "description": "", "description_tooltip": null, "layout": "IPY_MODEL_70a0b21c05e642e5891bb8b91cfb2217", - "placeholder": "\u200b", + "placeholder": "​", "style": "IPY_MODEL_444aa81458bf4790915c188069506864", - "value": "tokenizer.model:\u2007100%" + "value": "tokenizer.model: 100%" } }, "859b75a69281413383fc1c0946bf63d0": { @@ -4335,9 +4363,9 @@ "description": "", "description_tooltip": null, "layout": "IPY_MODEL_02d6b8e9a02b470a92f700d9e7fea5d4", - "placeholder": "\u200b", + "placeholder": "​", "style": "IPY_MODEL_8464d2f310b045808bcd7206aa7c8cc5", - "value": "Generating\u2007test\u2007split:\u2007100%" + "value": "Generating test split: 100%" } }, "8a21cb24786049e2946c9a050a6673ab": { @@ -4408,9 +4436,9 @@ "description": "", "description_tooltip": null, "layout": "IPY_MODEL_0c96fa0b7ed344f4be44632451b406d7", - "placeholder": "\u200b", + "placeholder": "​", "style": "IPY_MODEL_bf96f070c2f54468a674f11681fcb22d", - "value": "\u20072.31M/2.31M\u2007[00:00<00:00,\u200717.7MB/s]" + "value": " 2.31M/2.31M [00:00<00:00, 17.7MB/s]" } }, "8ca7d620dc5d415a83b50f134317d925": { @@ -4802,9 +4830,9 @@ "description": "", "description_tooltip": null, "layout": "IPY_MODEL_67eda18557dc461483821ffd44a25eb4", - "placeholder": "\u200b", + "placeholder": "​", "style": "IPY_MODEL_4cabdb178b97464e875d507dd1410bbf", - "value": "\u20077.94k/7.94k\u2007[00:00<00:00,\u2007179kB/s]" + "value": " 7.94k/7.94k [00:00<00:00, 179kB/s]" } }, "9e7bb56731134d9cba89cbde208358e0": { @@ -5024,9 +5052,9 @@ "description": "", "description_tooltip": null, "layout": "IPY_MODEL_def9dbef26334436a6b2298b5b153f47", - "placeholder": "\u200b", + "placeholder": "​", "style": "IPY_MODEL_eea838fbfd2c4e82b1769fde1036487e", - "value": "\u20074.69M/4.69M\u2007[00:00<00:00,\u200726.2MB/s]" + "value": " 4.69M/4.69M [00:00<00:00, 26.2MB/s]" } }, "a9dbcb0e164544ba8321a7916500009d": { @@ -5201,9 +5229,9 @@ "description": "", "description_tooltip": null, "layout": "IPY_MODEL_45aa2714bf0b44e9af7668c674f63863", - "placeholder": "\u200b", + "placeholder": "​", "style": "IPY_MODEL_8ca7d620dc5d415a83b50f134317d925", - "value": "\u2007215/215\u2007[00:00<00:00,\u200713.4kB/s]" + "value": " 215/215 [00:00<00:00, 13.4kB/s]" } }, "b0c51c819fff44c5a6e8e626fec9e937": { @@ -5237,9 +5265,9 @@ "description": "", "description_tooltip": null, "layout": "IPY_MODEL_d9e72108a08b447ea2a29932391fe429", - "placeholder": "\u200b", + "placeholder": "​", "style": "IPY_MODEL_21366789f69d431bad2ac2c8d1ec1565", - "value": "\u20072.00G/2.00G\u2007[00:15<00:00,\u200771.2MB/s]" + "value": " 2.00G/2.00G [00:15<00:00, 71.2MB/s]" } }, "b67486cb78274f2baa4f9afdc2fd7e3c": { @@ -5258,9 +5286,9 @@ "description": "", "description_tooltip": null, "layout": "IPY_MODEL_21f2aec6d7af4c3a82306ad235674829", - "placeholder": "\u200b", + "placeholder": "​", "style": "IPY_MODEL_fd6ff32a3aa7479e8b5d0cda47819742", - "value": "model.safetensors:\u2007100%" + "value": "model.safetensors: 100%" } }, "ba4ac2596dda42698ae048f9b7a11c61": { @@ -5839,9 +5867,9 @@ "description": "", "description_tooltip": null, "layout": "IPY_MODEL_8029855dfa614963a7f5ff11d48dcbdb", - "placeholder": "\u200b", + "placeholder": "​", "style": "IPY_MODEL_e74fcfb683074f27806b6aaae329b74d", - "value": "\u2007670/670\u2007[00:00<00:00,\u200774.3kB/s]" + "value": " 670/670 [00:00<00:00, 74.3kB/s]" } }, "d7b48dafe15947c9b225681c4a326581": { @@ -5949,9 +5977,9 @@ "description": "", "description_tooltip": null, "layout": "IPY_MODEL_a9dbcb0e164544ba8321a7916500009d", - "placeholder": "\u200b", + "placeholder": "​", "style": "IPY_MODEL_a6030d7b5bbd460fb5aa1356c607ec82", - "value": "\u2007419k/419k\u2007[00:00<00:00,\u20079.62MB/s]" + "value": " 419k/419k [00:00<00:00, 9.62MB/s]" } }, "def9dbef26334436a6b2298b5b153f47": { @@ -6089,9 +6117,9 @@ "description": "", "description_tooltip": null, "layout": "IPY_MODEL_25c7874a020344e7aad2869f7a27db4e", - "placeholder": "\u200b", + "placeholder": "​", "style": "IPY_MODEL_86e9660b2d72460c836d9bba348be56b", - "value": "\u20071319/1319\u2007[00:00<00:00,\u200712220.76\u2007examples/s]" + "value": " 1319/1319 [00:00<00:00, 12220.76 examples/s]" } }, "ed53e921682348b28e2be40eaf96cbf7": { @@ -6134,9 +6162,9 @@ "description": "", "description_tooltip": null, "layout": "IPY_MODEL_185b378797334c819f8a199760cac945", - 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"placeholder": "\u200b", + "placeholder": "​", "style": "IPY_MODEL_8f2974213b954318902d39a1fda9b3fb", - "value": "\u20077473/7473\u2007[00:00<00:00,\u20079263.20\u2007examples/s]" + "value": " 7473/7473 [00:00<00:00, 9263.20 examples/s]" } }, "f73516b2403f411d925618cfa2af5f46": { @@ -6436,4 +6464,4 @@ }, "nbformat": 4, "nbformat_minor": 0 -} \ No newline at end of file +} diff --git a/nb/Kaggle-Gemma3N_(4B)-Audio.ipynb b/nb/Kaggle-Gemma3N_(4B)-Audio.ipynb index 1689f8af..7dcae2b7 100644 --- a/nb/Kaggle-Gemma3N_(4B)-Audio.ipynb +++ b/nb/Kaggle-Gemma3N_(4B)-Audio.ipynb @@ -8,7 +8,7 @@ "
\n", "\n", "\n", - " Join Discord if you need help + \u2b50 Star us on Github \u2b50\n", + " Join Discord if you need help + ⭐ Star us on Github ⭐\n", "
\n", "\n", "To install Unsloth your local device, follow [our guide](https://docs.unsloth.ai/get-started/install-and-update). This notebook is licensed [LGPL-3.0](https://github.com/unslothai/notebooks?tab=LGPL-3.0-1-ov-file#readme).\n", @@ -51,7 +51,17 @@ "execution_count": null, "metadata": {}, "outputs": [], - "source": "%%capture\nimport os\n\n!pip install pip3-autoremove\n!pip install torch torchvision torchaudio xformers --index-url https://download.pytorch.org/whl/cu128\n!pip install unsloth\n!pip install transformers==4.56.2\n!pip install --no-deps trl==0.22.2\nimport torch; torch._dynamo.config.recompile_limit = 64;\n" + "source": [ + "%%capture\n", + "import os\n", + "\n", + "!pip install pip3-autoremove\n", + "!pip install torch torchvision torchaudio xformers --index-url https://download.pytorch.org/whl/cu128\n", + "!pip install unsloth\n", + "!pip install transformers==4.56.2\n", + "!pip install --no-deps trl==0.22.2\n", + "import torch; torch._dynamo.config.recompile_limit = 64;\n" + ] }, { "cell_type": "code", @@ -111,8 +121,8 @@ "name": "stdout", "output_type": "stream", "text": [ - "\ud83e\udda5 Unsloth: Will patch your computer to enable 2x faster free finetuning.\n", - "\ud83e\udda5 Unsloth Zoo will now patch everything to make training faster!\n", + "🦥 Unsloth: Will patch your computer to enable 2x faster free finetuning.\n", + "🦥 Unsloth Zoo will now patch everything to make training faster!\n", "==((====))== Unsloth 2025.7.5: Fast Gemma3N patching. Transformers: 4.54.0.dev0.\n", " \\\\ /| Tesla T4. Num GPUs = 1. Max memory: 14.741 GB. Platform: Linux.\n", "O^O/ \\_/ \\ Torch: 2.6.0+cu124. CUDA: 7.5. CUDA Toolkit: 12.4. Triton: 3.2.0\n", @@ -269,7 +279,7 @@ "name": "stdout", "output_type": "stream", "text": [ - " Ich, ich rechne direkt mich an. Das ist nat\u00fcrlich klar, nur, dass, \u00e4h, es politische Interessen gibt im Handel, im Austausch mit Waren, dass es politische Einfl\u00fcsse gibt. Die Frage ist, die Alternative soll es nicht sein.\n" + " Ich, ich rechne direkt mich an. Das ist natürlich klar, nur, dass, äh, es politische Interessen gibt im Handel, im Austausch mit Waren, dass es politische Einflüsse gibt. Die Frage ist, die Alternative soll es nicht sein.\n" ] }, { @@ -320,7 +330,7 @@ "name": "stdout", "output_type": "stream", "text": [ - "Sie direkt mich an. Das finde ich klar, nur dass es politisch Interessen gibt im Handel, im Austausch mit Waren, dass es politische Einfl\u00fcsse gibt. Die Frage ist, die Alternative soll es nicht sein.\n" + "Sie direkt mich an. Das finde ich klar, nur dass es politisch Interessen gibt im Handel, im Austausch mit Waren, dass es politische Einflüsse gibt. Die Frage ist, die Alternative soll es nicht sein.\n" ] } ], @@ -1426,7 +1436,7 @@ "name": "stdout", "output_type": "stream", "text": [ - "Du sprichst direkt mich an. Das finde ich klar, nur, dass, \u00e4h, dass politische Interessen gibt im Handel, im Austausch mit Waren, dass es politische Einfl\u00fcsse gibt. Die Frage ist, die Alternative soll es nicht sein.\n" + "Du sprichst direkt mich an. Das finde ich klar, nur, dass, äh, dass politische Interessen gibt im Handel, im Austausch mit Waren, dass es politische Einflüsse gibt. Die Frage ist, die Alternative soll es nicht sein.\n" ] } ], @@ -1641,10 +1651,9 @@ "source": [ "if False: # Change to True to upload GGUF\n", " model.push_to_hub_gguf(\n", - " \"gemma-3N-finetune\",\n", + " \"HF_ACCOUNT/gemma-3N-finetune-gguf\",\n", " processor,\n", " quantization_method = \"Q8_0\", # Only Q8_0, BF16, F16 supported\n", - " repo_id = \"HF_ACCOUNT/gemma-3N-finetune-gguf\",\n", " token = \"hf_...\",\n", " )" ] @@ -1670,9 +1679,10 @@ " \n", " \n", "\n", - " Join Discord if you need help + \u2b50\ufe0f Star us on Github \u2b50\ufe0f\n", + " Join Discord if you need help + ⭐️ Star us on Github ⭐️\n", "\n", - "\n This notebook and all Unsloth notebooks are licensed [LGPL-3.0](https://github.com/unslothai/notebooks?tab=LGPL-3.0-1-ov-file#readme).\n" + "\n", + " This notebook and all Unsloth notebooks are licensed [LGPL-3.0](https://github.com/unslothai/notebooks?tab=LGPL-3.0-1-ov-file#readme).\n" ] } ], @@ -1793,9 +1803,9 @@ "description": "", "description_tooltip": null, "layout": "IPY_MODEL_dd596d7ce92847178805247ed2ea2902", - "placeholder": "\u200b", + "placeholder": "​", "style": "IPY_MODEL_56256ba8e73c48898b147d2b91f4fd85", - "value": "Loading\u2007checkpoint\u2007shards:\u2007100%" + "value": "Loading checkpoint shards: 100%" } }, "54cedbd8ef984f6a89590f1651804c03": { @@ -1881,9 +1891,9 @@ "description": "", "description_tooltip": null, "layout": "IPY_MODEL_9d544cff64354e6695e90cfd70743d72", - "placeholder": "\u200b", + "placeholder": "​", "style": "IPY_MODEL_3e16f926611b458fbfa21f75bd8de2c2", - "value": "Map\u2007(num_proc=4):\u2007100%" + "value": "Map (num_proc=4): 100%" } }, "6dbca67a4bcf491fa0cdc07f10cca9c2": { @@ -2352,9 +2362,9 @@ "description": "", "description_tooltip": null, "layout": "IPY_MODEL_2d0675287f864fbdac1ca1439bc50077", - "placeholder": "\u200b", + "placeholder": "​", "style": "IPY_MODEL_8ef02bdc9627427d83a6324cb59c445e", - "value": "\u20073/3\u2007[00:39<00:00,\u200711.72s/it]" + "value": " 3/3 [00:39<00:00, 11.72s/it]" } }, "ecbee91d79834a49ab0cb3e33522d8d2": { @@ -2389,9 +2399,9 @@ "description": "", "description_tooltip": null, "layout": "IPY_MODEL_54cedbd8ef984f6a89590f1651804c03", - "placeholder": "\u200b", + "placeholder": "​", "style": "IPY_MODEL_9fdf6d3312be4f51912561ae1cb5a893", - "value": "\u20073000/3000\u2007[09:19<00:00,\u2007\u20073.22\u2007examples/s]" + "value": " 3000/3000 [09:19<00:00,  3.22 examples/s]" } }, "state": {} @@ -2400,4 +2410,4 @@ }, "nbformat": 4, "nbformat_minor": 0 -} \ No newline at end of file +} diff --git a/nb/Kaggle-Gemma3N_(4B)-Conversational.ipynb b/nb/Kaggle-Gemma3N_(4B)-Conversational.ipynb index 369fd9f5..3f85422f 100644 --- a/nb/Kaggle-Gemma3N_(4B)-Conversational.ipynb +++ b/nb/Kaggle-Gemma3N_(4B)-Conversational.ipynb @@ -8,7 +8,7 @@ "
\n", "\n", "\n", - " Join Discord if you need help + \u2b50 Star us on Github \u2b50\n", + " Join Discord if you need help + ⭐ Star us on Github ⭐\n", "
\n", "\n", "To install Unsloth your local device, follow [our guide](https://docs.unsloth.ai/get-started/install-and-update). This notebook is licensed [LGPL-3.0](https://github.com/unslothai/notebooks?tab=LGPL-3.0-1-ov-file#readme).\n", @@ -51,7 +51,17 @@ "execution_count": null, "metadata": {}, "outputs": [], - "source": "%%capture\nimport os\n\n!pip install pip3-autoremove\n!pip install torch torchvision torchaudio xformers --index-url https://download.pytorch.org/whl/cu128\n!pip install unsloth\n!pip install transformers==4.56.2\n!pip install --no-deps trl==0.22.2\nimport torch; torch._dynamo.config.recompile_limit = 64;\n" + "source": [ + "%%capture\n", + "import os\n", + "\n", + "!pip install pip3-autoremove\n", + "!pip install torch torchvision torchaudio xformers --index-url https://download.pytorch.org/whl/cu128\n", + "!pip install unsloth\n", + "!pip install transformers==4.56.2\n", + "!pip install --no-deps trl==0.22.2\n", + "import torch; torch._dynamo.config.recompile_limit = 64;\n" + ] }, { "cell_type": "code", @@ -237,8 +247,8 @@ "name": "stdout", "output_type": "stream", "text": [ - "\ud83e\udda5 Unsloth: Will patch your computer to enable 2x faster free finetuning.\n", - "\ud83e\udda5 Unsloth Zoo will now patch everything to make training faster!\n", + "🦥 Unsloth: Will patch your computer to enable 2x faster free finetuning.\n", + "🦥 Unsloth Zoo will now patch everything to make training faster!\n", "==((====))== Unsloth 2025.6.12: Fast Gemma3N patching. Transformers: 4.54.0.dev0.\n", " \\\\ /| Tesla T4. Num GPUs = 1. Max memory: 14.741 GB. Platform: Linux.\n", "O^O/ \\_/ \\ Torch: 2.6.0+cu124. CUDA: 7.5. CUDA Toolkit: 12.4. Triton: 3.2.0\n", @@ -2035,10 +2045,9 @@ "source": [ "if False: # Change to True to upload GGUF\n", " model.push_to_hub_gguf(\n", - " \"gemma-3N-finetune\",\n", + " \"HF_ACCOUNT/gemma-3N-finetune-gguf\",\n", " tokenizer,\n", " quantization_method = \"Q8_0\", # Only Q8_0, BF16, F16 supported\n", - " repo_id = \"HF_ACCOUNT/gemma-3N-finetune-gguf\",\n", " token = \"hf_...\",\n", " )" ] @@ -2064,9 +2073,10 @@ " \n", " \n", "\n", - " Join Discord if you need help + \u2b50\ufe0f Star us on Github \u2b50\ufe0f\n", + " Join Discord if you need help + ⭐️ Star us on Github ⭐️\n", "\n", - "\n This notebook and all Unsloth notebooks are licensed [LGPL-3.0](https://github.com/unslothai/notebooks?tab=LGPL-3.0-1-ov-file#readme).\n" + "\n", + " This notebook and all Unsloth notebooks are licensed [LGPL-3.0](https://github.com/unslothai/notebooks?tab=LGPL-3.0-1-ov-file#readme).\n" ] } ], @@ -2112,9 +2122,9 @@ "description": "", "description_tooltip": null, "layout": "IPY_MODEL_d66ecbc2c4664427bb85cb4a3ae629a4", - 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"placeholder": "\u200b", + "placeholder": "​", "style": "IPY_MODEL_48fa153e76e84a2891a406d381b25ad3", - "value": "\u20074.70M/4.70M\u2007[00:00<00:00,\u20079.78MB/s]" + "value": " 4.70M/4.70M [00:00<00:00, 9.78MB/s]" } }, "state": {} @@ -8942,4 +8952,4 @@ }, "nbformat": 4, "nbformat_minor": 0 -} \ No newline at end of file +} diff --git a/nb/Kaggle-Gemma3_(1B)-GRPO.ipynb b/nb/Kaggle-Gemma3_(1B)-GRPO.ipynb index 6b4da08e..9e9f25e9 100644 --- a/nb/Kaggle-Gemma3_(1B)-GRPO.ipynb +++ b/nb/Kaggle-Gemma3_(1B)-GRPO.ipynb @@ -8,7 +8,7 @@ "
\n", "\n", "\n", - " Join Discord if you need help + \u2b50 Star us on Github \u2b50\n", + " Join Discord if you need help + ⭐ Star us on Github ⭐\n", "
\n", "\n", "To install Unsloth your local device, follow [our guide](https://docs.unsloth.ai/get-started/install-and-update). This notebook is licensed [LGPL-3.0](https://github.com/unslothai/notebooks?tab=LGPL-3.0-1-ov-file#readme).\n", @@ -51,7 +51,22 @@ "execution_count": null, "metadata": {}, "outputs": [], - "source": "%%capture\nimport os\nos.environ[\"UNSLOTH_VLLM_STANDBY\"] = \"1\" # [NEW] Extra 30% context lengths!\n!pip install --upgrade -qqq uv\ntry: import numpy, PIL; get_numpy = f\"numpy=={numpy.__version__}\"; get_pil = f\"pillow=={PIL.__version__}\"\nexcept: get_numpy = \"numpy\"; get_pil = \"pillow\"\ntry: import subprocess; is_t4 = \"Tesla T4\" in str(subprocess.check_output([\"nvidia-smi\"]))\nexcept: is_t4 = False\nget_vllm, get_triton = (\"vllm==0.9.2\", \"triton==3.2.0\") if is_t4 else (\"vllm==0.10.2\", \"triton\")\n!uv pip install -qqq --upgrade unsloth {get_vllm} {get_numpy} {get_pil} torchvision bitsandbytes xformers\n!uv pip install -qqq {get_triton}\n!uv pip install \"huggingface_hub>=0.34.0\" \"datasets>=3.4.1,<4.0.\n!uv pip install transformers==4.56.2\n!uv pip install --no-deps trl==0.22.2" + "source": [ + "%%capture\n", + "import os\n", + "os.environ[\"UNSLOTH_VLLM_STANDBY\"] = \"1\" # [NEW] Extra 30% context lengths!\n", + "!pip install --upgrade -qqq uv\n", + "try: import numpy, PIL; get_numpy = f\"numpy=={numpy.__version__}\"; get_pil = f\"pillow=={PIL.__version__}\"\n", + "except: get_numpy = \"numpy\"; get_pil = \"pillow\"\n", + "try: import subprocess; is_t4 = \"Tesla T4\" in str(subprocess.check_output([\"nvidia-smi\"]))\n", + "except: is_t4 = False\n", + "get_vllm, get_triton = (\"vllm==0.9.2\", \"triton==3.2.0\") if is_t4 else (\"vllm==0.10.2\", \"triton\")\n", + "!uv pip install -qqq --upgrade unsloth {get_vllm} {get_numpy} {get_pil} torchvision bitsandbytes xformers\n", + "!uv pip install -qqq {get_triton}\n", + "!uv pip install \"huggingface_hub>=0.34.0\" \"datasets>=3.4.1,<4.0.\n", + "!uv pip install transformers==4.56.2\n", + "!uv pip install --no-deps trl==0.22.2" + ] }, { "cell_type": "markdown", @@ -166,8 +181,8 @@ "name": "stdout", "output_type": "stream", "text": [ - "\ud83e\udda5 Unsloth: Will patch your computer to enable 2x faster free finetuning.\n", - "\ud83e\udda5 Unsloth Zoo will now patch everything to make training faster!\n", + "🦥 Unsloth: Will patch your computer to enable 2x faster free finetuning.\n", + "🦥 Unsloth Zoo will now patch everything to make training faster!\n", "INFO 03-19 15:51:40 [__init__.py:256] Automatically detected platform cuda.\n", "==((====))== Unsloth 2025.3.17: Fast Gemma3 patching. Transformers: 4.50.0.dev0. vLLM: 0.8.0.\n", " \\\\ /| Tesla T4. Num GPUs = 1. Max memory: 14.741 GB. Platform: Linux.\n", @@ -1360,15 +1375,15 @@ "Loan amount: $480,000\n", "Interest rate: We need to assume an interest rate for this problem. Let's assume an annual interest rate of 6% (this is a common rate).\n", "Loan term: 20 years, so 20 * 12 = 240 months\n", - "We will use the loan payment formula: M = P [ i(1 + i)^n ] / [ (1 + i)^n \u2013 1]\n", + "We will use the loan payment formula: M = P [ i(1 + i)^n ] / [ (1 + i)^n – 1]\n", "where M is the monthly payment, P is the loan amount, i is the monthly interest rate, and n is the number of months.\n", "\n", "Monthly interest rate (i) = Annual interest rate / 12 = 0.06 / 12 = 0.005\n", "Number of months (n) = 240\n", "\n", - "M = 480000 [ 0.005(1 + 0.005)^240 ] / [ (1 + 0.005)^240 \u2013 1]\n", - "M = 480000 [ 0.005(1.005)^240 ] / [ (1.005)^240 \u2013 1]\n", - "M = 480000 [ 0.005 * 3.310853] / [ 3.310853 \u2013 1]\n", + "M = 480000 [ 0.005(1 + 0.005)^240 ] / [ (1 + 0.005)^240 – 1]\n", + "M = 480000 [ 0.005(1.005)^240 ] / [ (1.005)^240 – 1]\n", + "M = 480000 [ 0.005 * 3.310853] / [ 3.310853 – 1]\n", "M = 480000 [ 0.016554265] / [2.310853]\n", "M = 480000 * 0.00703658\n", "M = $331.54\n", @@ -1377,15 +1392,15 @@ "Loan amount: $120,000\n", "Interest rate: We still assume an annual interest rate of 6% (this is a common rate).\n", "Loan term: 20 years, so 20 * 12 = 240 months\n", - "We will use the loan payment formula: M = P [ i(1 + i)^n ] / [ (1 + i)^n \u2013 1]\n", + "We will use the loan payment formula: M = P [ i(1 + i)^n ] / [ (1 + i)^n – 1]\n", "where M is the monthly payment, P is the loan amount, i is the monthly interest rate, and n is the number of months.\n", "\n", "Monthly interest rate (i) = Annual interest rate / 12 = 0.06 / 12 = 0.005\n", "Number of months (n) = 240\n", "\n", - "M = 120000 [ 0.005(1 + 0.005)^240 ] / [ (1 + 0.005)^240 \u2013 1]\n", - "M = 120000 [ 0.005(1.005)^240 ] / [ (1.005)^240 \u2013 1]\n", - "M = 120000 [ 0.005 * 3.310853 ] / [ 3.310853 \u2013 1]\n", + "M = 120000 [ 0.005(1 + 0.005)^240 ] / [ (1 + 0.005)^240 – 1]\n", + "M = 120000 [ 0.005(1.005)^240 ] / [ (1.005)^240 – 1]\n", + "M = 120000 [ 0.005 * 3.310853 ] / [ 3.310853 – 1]\n", "M = 120000 [ 0.016554265] / [2.310853]\n", "M = 1200 \n", "Extracted:\n", @@ -1922,10 +1937,9 @@ "source": [ "if False: # Change to True to upload GGUF\n", " model.push_to_hub_gguf(\n", - " \"gemma-3-finetune\",\n", + " \"HF_ACCOUNT/gemma-finetune-gguf\",\n", " tokenizer,\n", " quantization_method = \"Q8_0\", # Only Q8_0, BF16, F16 supported\n", - " repo_id = \"HF_ACCOUNT/gemma-finetune-gguf\",\n", " token = \"hf_...\",\n", " )" ] @@ -1951,9 +1965,10 @@ " \n", " \n", "\n", - " Join Discord if you need help + \u2b50\ufe0f Star us on Github \u2b50\ufe0f\n", + " Join Discord if you need help + ⭐️ Star us on Github ⭐️\n", "\n", - "\n This notebook and all Unsloth notebooks are licensed [LGPL-3.0](https://github.com/unslothai/notebooks?tab=LGPL-3.0-1-ov-file#readme).\n" + "\n", + " This notebook and all Unsloth notebooks are licensed [LGPL-3.0](https://github.com/unslothai/notebooks?tab=LGPL-3.0-1-ov-file#readme).\n" ] } ], @@ -2231,9 +2246,9 @@ "description": "", "description_tooltip": null, "layout": "IPY_MODEL_551b94fe4b3c4a4f8f3220d013a6d897", - "placeholder": "\u200b", + "placeholder": "​", "style": "IPY_MODEL_29d36346bc75470eacd30aebf1423e14", - "value": "tokenizer.json:\u2007100%" + "value": "tokenizer.json: 100%" } }, "0ef32700424c4799b8216de4ed8bbbb9": { @@ -2343,9 +2358,9 @@ "description": "", "description_tooltip": null, "layout": "IPY_MODEL_383d2f04eccd4e38ad791494a06423ed", - "placeholder": "\u200b", + "placeholder": "​", "style": "IPY_MODEL_36cabdee7cd645a58e1ffc794674a322", - "value": "special_tokens_map.json:\u2007100%" + "value": "special_tokens_map.json: 100%" } }, "1664b23faa1b4292bb5727bd525c45be": { @@ -2438,9 +2453,9 @@ "description": "", "description_tooltip": null, "layout": "IPY_MODEL_772360d1551141c5ab0a877ae4ed1c76", - "placeholder": "\u200b", + "placeholder": "​", "style": "IPY_MODEL_b0c51c819fff44c5a6e8e626fec9e937", - "value": "tokenizer_config.json:\u2007100%" + "value": "tokenizer_config.json: 100%" } }, "19731cf654e64eb3905f02f4ae277e8c": { @@ -2835,9 +2850,9 @@ "description": "", "description_tooltip": null, "layout": "IPY_MODEL_6decae16dd5b404ba272d89df9c1372b", - "placeholder": "\u200b", + "placeholder": "​", "style": "IPY_MODEL_9151ae8e05634cf4a8ce42677f211bac", - "value": "Map:\u2007100%" + "value": "Map: 100%" } }, "340c07f1b7b14527a378880f9166ef55": { @@ -2993,9 +3008,9 @@ "description": "", "description_tooltip": null, "layout": "IPY_MODEL_671b4725f18a4c809b3c97a65ec9e405", - "placeholder": "\u200b", + "placeholder": "​", "style": "IPY_MODEL_faa61469d4bc46aebe74d5401d42c3ab", - "value": "\u200735.0/35.0\u2007[00:00<00:00,\u20072.66kB/s]" + "value": " 35.0/35.0 [00:00<00:00, 2.66kB/s]" } }, "3fabb349d1f943b09ed25784a0d0ab0a": { @@ -3318,9 +3333,9 @@ "description": "", "description_tooltip": null, "layout": "IPY_MODEL_cf83a6e558f64ff98276981a82f3b2ac", - "placeholder": "\u200b", + "placeholder": "​", "style": "IPY_MODEL_0ef32700424c4799b8216de4ed8bbbb9", - "value": "test-00000-of-00001.parquet:\u2007100%" + "value": "test-00000-of-00001.parquet: 100%" } }, "50503005b58845b79254f89f95fb03d9": { @@ -3363,9 +3378,9 @@ "description": "", "description_tooltip": null, "layout": "IPY_MODEL_d1e38bbf7593462bb87b14bacee9e3d9", - "placeholder": "\u200b", + "placeholder": "​", "style": "IPY_MODEL_846c1dd9b3214c68bbfc362166a6b9ee", - "value": "\u20077473/7473\u2007[00:00<00:00,\u20075203.68\u2007examples/s]" + "value": " 7473/7473 [00:00<00:00, 5203.68 examples/s]" } }, "54c603df4e174b70bd03bce59de287b2": { @@ -3476,9 +3491,9 @@ "description": "", "description_tooltip": null, "layout": "IPY_MODEL_9677dc2a2f4847d89d3ca42c01435205", - "placeholder": "\u200b", + "placeholder": "​", "style": "IPY_MODEL_645b707de96a4c2eb07eb118db311fb6", - "value": "Generating\u2007train\u2007split:\u2007100%" + "value": "Generating train split: 100%" } }, "61d7ca5d56f14d7d93d5cf5e5b712da2": { @@ -4025,9 +4040,9 @@ "description": "", "description_tooltip": null, "layout": "IPY_MODEL_669cb00554134e8287d0daae7372d397", - "placeholder": "\u200b", + "placeholder": "​", "style": "IPY_MODEL_9e7bb56731134d9cba89cbde208358e0", - "value": "train-00000-of-00001.parquet:\u2007100%" + "value": "train-00000-of-00001.parquet: 100%" } }, "7c4cd321445b43bfa818b599d42c8cb7": { @@ -4046,9 +4061,9 @@ "description": "", "description_tooltip": null, "layout": "IPY_MODEL_cec948b41ee348fcbdf2f5fa290ffe42", - "placeholder": "\u200b", + "placeholder": "​", "style": "IPY_MODEL_6d1b19657db94907b6fdf0a3b3a05e84", - "value": "README.md:\u2007100%" + "value": "README.md: 100%" } }, "7d4b49f0c54046a89039d25ee7c11f6f": { @@ -4223,9 +4238,9 @@ "description": "", "description_tooltip": null, "layout": "IPY_MODEL_1da84b32592d432fb1a57358ddcdceff", - "placeholder": "\u200b", + "placeholder": "​", "style": "IPY_MODEL_bbcd20b75ce445bea7be9597efa68d73", - "value": "\u200733.4M/33.4M\u2007[00:00<00:00,\u2007144MB/s]" + "value": " 33.4M/33.4M [00:00<00:00, 144MB/s]" } }, "8464d2f310b045808bcd7206aa7c8cc5": { @@ -4274,9 +4289,9 @@ "description": "", "description_tooltip": null, "layout": "IPY_MODEL_70a0b21c05e642e5891bb8b91cfb2217", - "placeholder": "\u200b", + "placeholder": "​", "style": "IPY_MODEL_444aa81458bf4790915c188069506864", - "value": "tokenizer.model:\u2007100%" + "value": "tokenizer.model: 100%" } }, "859b75a69281413383fc1c0946bf63d0": { @@ -4326,9 +4341,9 @@ "description": "", "description_tooltip": null, "layout": "IPY_MODEL_02d6b8e9a02b470a92f700d9e7fea5d4", - "placeholder": "\u200b", + "placeholder": "​", "style": "IPY_MODEL_8464d2f310b045808bcd7206aa7c8cc5", - "value": "Generating\u2007test\u2007split:\u2007100%" + "value": "Generating test split: 100%" } }, "8a21cb24786049e2946c9a050a6673ab": { @@ -4399,9 +4414,9 @@ "description": "", "description_tooltip": null, "layout": "IPY_MODEL_0c96fa0b7ed344f4be44632451b406d7", - "placeholder": "\u200b", + "placeholder": "​", "style": "IPY_MODEL_bf96f070c2f54468a674f11681fcb22d", - "value": "\u20072.31M/2.31M\u2007[00:00<00:00,\u200717.7MB/s]" + "value": " 2.31M/2.31M [00:00<00:00, 17.7MB/s]" } }, "8ca7d620dc5d415a83b50f134317d925": { @@ -4793,9 +4808,9 @@ "description": "", "description_tooltip": null, "layout": "IPY_MODEL_67eda18557dc461483821ffd44a25eb4", - "placeholder": "\u200b", + "placeholder": "​", "style": "IPY_MODEL_4cabdb178b97464e875d507dd1410bbf", - "value": "\u20077.94k/7.94k\u2007[00:00<00:00,\u2007179kB/s]" + "value": " 7.94k/7.94k [00:00<00:00, 179kB/s]" } }, "9e7bb56731134d9cba89cbde208358e0": { @@ -5015,9 +5030,9 @@ "description": "", "description_tooltip": null, "layout": "IPY_MODEL_def9dbef26334436a6b2298b5b153f47", - "placeholder": "\u200b", + "placeholder": "​", "style": "IPY_MODEL_eea838fbfd2c4e82b1769fde1036487e", - "value": "\u20074.69M/4.69M\u2007[00:00<00:00,\u200726.2MB/s]" + "value": " 4.69M/4.69M [00:00<00:00, 26.2MB/s]" } }, "a9dbcb0e164544ba8321a7916500009d": { @@ -5192,9 +5207,9 @@ "description": "", "description_tooltip": null, "layout": "IPY_MODEL_45aa2714bf0b44e9af7668c674f63863", - "placeholder": "\u200b", + "placeholder": "​", "style": "IPY_MODEL_8ca7d620dc5d415a83b50f134317d925", - "value": "\u2007215/215\u2007[00:00<00:00,\u200713.4kB/s]" + "value": " 215/215 [00:00<00:00, 13.4kB/s]" } }, "b0c51c819fff44c5a6e8e626fec9e937": { @@ -5228,9 +5243,9 @@ "description": "", "description_tooltip": null, "layout": "IPY_MODEL_d9e72108a08b447ea2a29932391fe429", - "placeholder": "\u200b", + "placeholder": "​", "style": "IPY_MODEL_21366789f69d431bad2ac2c8d1ec1565", - "value": "\u20072.00G/2.00G\u2007[00:15<00:00,\u200771.2MB/s]" + "value": " 2.00G/2.00G [00:15<00:00, 71.2MB/s]" } }, "b67486cb78274f2baa4f9afdc2fd7e3c": { @@ -5249,9 +5264,9 @@ "description": "", "description_tooltip": null, "layout": "IPY_MODEL_21f2aec6d7af4c3a82306ad235674829", - "placeholder": "\u200b", + "placeholder": "​", "style": "IPY_MODEL_fd6ff32a3aa7479e8b5d0cda47819742", - "value": "model.safetensors:\u2007100%" + "value": "model.safetensors: 100%" } }, "ba4ac2596dda42698ae048f9b7a11c61": { @@ -5830,9 +5845,9 @@ "description": "", "description_tooltip": null, "layout": "IPY_MODEL_8029855dfa614963a7f5ff11d48dcbdb", - "placeholder": "\u200b", + "placeholder": "​", "style": "IPY_MODEL_e74fcfb683074f27806b6aaae329b74d", - "value": "\u2007670/670\u2007[00:00<00:00,\u200774.3kB/s]" + "value": " 670/670 [00:00<00:00, 74.3kB/s]" } }, "d7b48dafe15947c9b225681c4a326581": { @@ -5940,9 +5955,9 @@ "description": "", "description_tooltip": null, "layout": "IPY_MODEL_a9dbcb0e164544ba8321a7916500009d", - "placeholder": "\u200b", + "placeholder": "​", "style": "IPY_MODEL_a6030d7b5bbd460fb5aa1356c607ec82", - "value": "\u2007419k/419k\u2007[00:00<00:00,\u20079.62MB/s]" + "value": " 419k/419k [00:00<00:00, 9.62MB/s]" } }, "def9dbef26334436a6b2298b5b153f47": { @@ -6080,9 +6095,9 @@ "description": "", "description_tooltip": null, "layout": "IPY_MODEL_25c7874a020344e7aad2869f7a27db4e", - "placeholder": "\u200b", + "placeholder": "​", "style": "IPY_MODEL_86e9660b2d72460c836d9bba348be56b", - "value": "\u20071319/1319\u2007[00:00<00:00,\u200712220.76\u2007examples/s]" + "value": " 1319/1319 [00:00<00:00, 12220.76 examples/s]" } }, "ed53e921682348b28e2be40eaf96cbf7": { @@ -6125,9 +6140,9 @@ "description": "", "description_tooltip": null, "layout": "IPY_MODEL_185b378797334c819f8a199760cac945", - "placeholder": "\u200b", + "placeholder": "​", "style": "IPY_MODEL_a1fced067e1e40cbb08e25c9377123e0", - "value": "generation_config.json:\u2007100%" + "value": "generation_config.json: 100%" } }, "eea838fbfd2c4e82b1769fde1036487e": { @@ -6161,9 +6176,9 @@ "description": "", "description_tooltip": null, "layout": "IPY_MODEL_45eda31f22294728bbca360abad799e6", - "placeholder": "\u200b", + "placeholder": "​", "style": "IPY_MODEL_d7b48dafe15947c9b225681c4a326581", - "value": "\u20071.16M/1.16M\u2007[00:00<00:00,\u20076.41MB/s]" + "value": " 1.16M/1.16M [00:00<00:00, 6.41MB/s]" } }, "efaa563da24149aaaa153b7e8c473394": { @@ -6341,9 +6356,9 @@ "description": "", "description_tooltip": null, "layout": "IPY_MODEL_aaf739645f654cd6a94d897358b2c2e0", - "placeholder": "\u200b", + "placeholder": "​", "style": "IPY_MODEL_f0c1afb62d8a4616a8df27c9de866916", - "value": "added_tokens.json:\u2007100%" + "value": "added_tokens.json: 100%" } }, "f6a520e1570d4f7faffc1b6e2c6200d2": { @@ -6362,9 +6377,9 @@ "description": "", "description_tooltip": null, "layout": "IPY_MODEL_10c20527dc19466eb4d6eb325529a0df", - "placeholder": "\u200b", + "placeholder": "​", "style": "IPY_MODEL_8f2974213b954318902d39a1fda9b3fb", - "value": "\u20077473/7473\u2007[00:00<00:00,\u20079263.20\u2007examples/s]" + "value": " 7473/7473 [00:00<00:00, 9263.20 examples/s]" } }, "f73516b2403f411d925618cfa2af5f46": { @@ -6427,4 +6442,4 @@ }, "nbformat": 4, "nbformat_minor": 0 -} \ No newline at end of file +} diff --git a/nb/Kaggle-Gemma3_(270M).ipynb b/nb/Kaggle-Gemma3_(270M).ipynb index 865afe6f..c4cbb98e 100644 --- a/nb/Kaggle-Gemma3_(270M).ipynb +++ b/nb/Kaggle-Gemma3_(270M).ipynb @@ -8,7 +8,7 @@ "
\n", "\n", "\n", - " Join Discord if you need help + \u2b50 Star us on Github \u2b50\n", + " Join Discord if you need help + ⭐ Star us on Github ⭐\n", "
\n", "\n", "To install Unsloth your local device, follow [our guide](https://docs.unsloth.ai/get-started/install-and-update). This notebook is licensed [LGPL-3.0](https://github.com/unslothai/notebooks?tab=LGPL-3.0-1-ov-file#readme).\n", @@ -51,7 +51,16 @@ "execution_count": null, "metadata": {}, "outputs": [], - "source": "%%capture\nimport os\n\n!pip install pip3-autoremove\n!pip install torch torchvision torchaudio xformers --index-url https://download.pytorch.org/whl/cu128\n!pip install unsloth\n!pip install transformers==4.56.2\n!pip install --no-deps trl==0.22.2" + "source": [ + "%%capture\n", + "import os\n", + "\n", + "!pip install pip3-autoremove\n", + "!pip install torch torchvision torchaudio xformers --index-url https://download.pytorch.org/whl/cu128\n", + "!pip install unsloth\n", + "!pip install transformers==4.56.2\n", + "!pip install --no-deps trl==0.22.2" + ] }, { "cell_type": "markdown", @@ -170,8 +179,8 @@ "name": "stdout", "output_type": "stream", "text": [ - "\ud83e\udda5 Unsloth: Will patch your computer to enable 2x faster free finetuning.\n", - "\ud83e\udda5 Unsloth Zoo will now patch everything to make training faster!\n", + "🦥 Unsloth: Will patch your computer to enable 2x faster free finetuning.\n", + "🦥 Unsloth Zoo will now patch everything to make training faster!\n", "==((====))== Unsloth 2025.8.9: Fast Gemma3 patching. Transformers: 4.55.2.\n", " \\\\ /| Tesla T4. Num GPUs = 1. Max memory: 14.741 GB. Platform: Linux.\n", "O^O/ \\_/ \\ Torch: 2.8.0+cu126. CUDA: 7.5. CUDA Toolkit: 12.6. Triton: 3.4.0\n", @@ -1723,7 +1732,7 @@ }, { "cell_type": "code", - "execution_count": 22, + "execution_count": null, "metadata": { "id": "S-TqCnZVu5Ll" }, @@ -1731,10 +1740,9 @@ "source": [ "if False: # Change to True to upload GGUF\n", " model.push_to_hub_gguf(\n", - " \"gemma-3-finetune\",\n", + " \"HF_ACCOUNT/gemma-finetune-gguf\",\n", " tokenizer,\n", " quantization_method = \"Q8_0\", # Only Q8_0, BF16, F16 supported\n", - " repo_id = \"HF_ACCOUNT/gemma-finetune-gguf\",\n", " token = \"hf_...\",\n", " )" ] @@ -1760,9 +1768,10 @@ " \n", " \n", "\n", - " Join Discord if you need help + \u2b50\ufe0f Star us on Github \u2b50\ufe0f\n", + " Join Discord if you need help + ⭐️ Star us on Github ⭐️\n", "\n", - "\n This notebook and all Unsloth notebooks are licensed [LGPL-3.0](https://github.com/unslothai/notebooks?tab=LGPL-3.0-1-ov-file#readme).\n" + "\n", + " This notebook and all Unsloth notebooks are licensed [LGPL-3.0](https://github.com/unslothai/notebooks?tab=LGPL-3.0-1-ov-file#readme).\n" ] } ], @@ -2128,9 +2137,9 @@ "description": "", "description_tooltip": null, "layout": "IPY_MODEL_e94421d86a43458897f4f66d91cd6989", - 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"placeholder": "\u200b", + "placeholder": "​", "style": "IPY_MODEL_afec33708ac1447abd9d163d33ea3fc2", - "value": "README.md:\u2007" + "value": "README.md: " } }, "f51ef90e456646b1be4437da9f1b8bd4": { @@ -7611,4 +7620,4 @@ }, "nbformat": 4, "nbformat_minor": 0 -} \ No newline at end of file +} diff --git a/nb/Kaggle-Gemma3_(27B)_A100-Conversational.ipynb b/nb/Kaggle-Gemma3_(27B)_A100-Conversational.ipynb index 0205427d..d72f6190 100644 --- a/nb/Kaggle-Gemma3_(27B)_A100-Conversational.ipynb +++ b/nb/Kaggle-Gemma3_(27B)_A100-Conversational.ipynb @@ -8,7 +8,7 @@ "
\n", "\n", "\n", - " Join Discord if you need help + \u2b50 Star us on Github \u2b50\n", + " Join Discord if you need help + ⭐ Star us on Github ⭐\n", "
\n", "\n", "To install Unsloth your local device, follow [our guide](https://docs.unsloth.ai/get-started/install-and-update). This notebook is licensed [LGPL-3.0](https://github.com/unslothai/notebooks?tab=LGPL-3.0-1-ov-file#readme).\n", @@ -51,7 +51,16 @@ "execution_count": null, "metadata": {}, "outputs": [], - "source": "%%capture\nimport os\n\n!pip install pip3-autoremove\n!pip install torch torchvision torchaudio xformers --index-url https://download.pytorch.org/whl/cu128\n!pip install unsloth\n!pip install transformers==4.56.2\n!pip install --no-deps trl==0.22.2" + "source": [ + "%%capture\n", + "import os\n", + "\n", + "!pip install pip3-autoremove\n", + "!pip install torch torchvision torchaudio xformers --index-url https://download.pytorch.org/whl/cu128\n", + "!pip install unsloth\n", + "!pip install transformers==4.56.2\n", + "!pip install --no-deps trl==0.22.2" + ] }, { "cell_type": "markdown", @@ -93,8 +102,8 @@ "name": "stdout", "output_type": "stream", "text": [ - "\ud83e\udda5 Unsloth: Will patch your computer to enable 2x faster free finetuning.\n", - "\ud83e\udda5 Unsloth Zoo will now patch everything to make training faster!\n", + "🦥 Unsloth: Will patch your computer to enable 2x faster free finetuning.\n", + "🦥 Unsloth Zoo will now patch everything to make training faster!\n", "==((====))== Unsloth 2025.9.1: Fast Gemma3 patching. Transformers: 4.55.4.\n", " \\\\ /| NVIDIA A100-SXM4-40GB. Num GPUs = 1. Max memory: 39.557 GB. Platform: Linux.\n", "O^O/ \\_/ \\ Torch: 2.8.0+cu126. CUDA: 8.0. CUDA Toolkit: 12.6. Triton: 3.4.0\n", @@ -1080,10 +1089,9 @@ "source": [ "if False: # Change to True to upload GGUF\n", " model.push_to_hub_gguf(\n", - " \"gemma-3-finetune\",\n", + " \"HF_ACCOUNT/gemma-finetune-gguf\",\n", " tokenizer,\n", " quantization_method = \"Q8_0\", # Only Q8_0, BF16, F16 supported\n", - " repo_id = \"HF_ACCOUNT/gemma-finetune-gguf\",\n", " token = \"hf_...\",\n", " )" ] @@ -1105,7 +1113,7 @@ " \n", " \n", "\n", - " Join Discord if you need help + \u2b50\ufe0f Star us on Github \u2b50\ufe0f\n", + " Join Discord if you need help + ⭐️ Star us on Github ⭐️\n", "\n", " This notebook and all Unsloth notebooks are licensed [LGPL-3.0](https://github.com/unslothai/notebooks?tab=LGPL-3.0-1-ov-file#readme)\n", "\n" @@ -1256,9 +1264,9 @@ "description": "", "description_tooltip": null, "layout": "IPY_MODEL_3ce1a50e1d624f4d9e679f148b4b31c7", - "placeholder": "\u200b", + "placeholder": "​", "style": "IPY_MODEL_ecd5db31b0604c09b7a86c5d578b3580", - "value": "\u20075/5\u2007[00:07<00:00,\u2007\u20071.17s/it]" + "value": " 5/5 [00:07<00:00,  1.17s/it]" } }, "3ce1a50e1d624f4d9e679f148b4b31c7": { @@ -1390,9 +1398,9 @@ "description": "", "description_tooltip": null, "layout": "IPY_MODEL_d2af8a2712bb42ab860ebda80da376bc", - "placeholder": "\u200b", + "placeholder": "​", "style": "IPY_MODEL_8524552679b94102b623aa616bbb9a02", - "value": "Loading\u2007checkpoint\u2007shards:\u2007100%" + "value": "Loading checkpoint shards: 100%" } }, "a254522d6e95440ea53f217785d98a4d": { @@ -1484,4 +1492,4 @@ }, "nbformat": 4, "nbformat_minor": 0 -} \ No newline at end of file +} diff --git a/nb/Kaggle-Gemma3_(4B).ipynb b/nb/Kaggle-Gemma3_(4B).ipynb index 8d9ff554..d667f003 100644 --- a/nb/Kaggle-Gemma3_(4B).ipynb +++ b/nb/Kaggle-Gemma3_(4B).ipynb @@ -8,7 +8,7 @@ "
\n", "\n", "\n", - " Join Discord if you need help + \u2b50 Star us on Github \u2b50\n", + " Join Discord if you need help + ⭐ Star us on Github ⭐\n", "
\n", "\n", "To install Unsloth your local device, follow [our guide](https://docs.unsloth.ai/get-started/install-and-update). This notebook is licensed [LGPL-3.0](https://github.com/unslothai/notebooks?tab=LGPL-3.0-1-ov-file#readme).\n", @@ -51,7 +51,16 @@ "execution_count": null, "metadata": {}, "outputs": [], - "source": "%%capture\nimport os\n\n!pip install pip3-autoremove\n!pip install torch torchvision torchaudio xformers --index-url https://download.pytorch.org/whl/cu128\n!pip install unsloth\n!pip install transformers==4.56.2\n!pip install --no-deps trl==0.22.2" + "source": [ + "%%capture\n", + "import os\n", + "\n", + "!pip install pip3-autoremove\n", + "!pip install torch torchvision torchaudio xformers --index-url https://download.pytorch.org/whl/cu128\n", + "!pip install unsloth\n", + "!pip install transformers==4.56.2\n", + "!pip install --no-deps trl==0.22.2" + ] }, { "cell_type": "markdown", @@ -192,9 +201,9 @@ "name": "stdout", "output_type": "stream", "text": [ - "\ud83e\udda5 Unsloth: Will patch your computer to enable 2x faster free finetuning.\n", + "🦥 Unsloth: Will patch your computer to enable 2x faster free finetuning.\n", "Unsloth: Successfully patched SmolVLMForConditionalGeneration for better torch.compile compatibility.\n", - "\ud83e\udda5 Unsloth Zoo will now patch everything to make training faster!\n", + "🦥 Unsloth Zoo will now patch everything to make training faster!\n", "==((====))== Unsloth 2025.3.19: Fast Gemma3 patching. Transformers: 4.50.2.\n", " \\\\ /| NVIDIA GeForce RTX 3060. Num GPUs = 1. Max memory: 11.755 GB. Platform: Linux.\n", "O^O/ \\_/ \\ Torch: 2.6.0+cu124. CUDA: 8.6. CUDA Toolkit: 12.4. Triton: 3.2.0\n", @@ -1308,10 +1317,9 @@ "source": [ "if False: # Change to True to upload GGUF\n", " model.push_to_hub_gguf(\n", - " \"gemma-3-finetune\",\n", + " \"HF_ACCOUNT/gemma-finetune-gguf\",\n", " tokenizer,\n", " quantization_method = \"Q8_0\", # Only Q8_0, BF16, F16 supported\n", - " repo_id = \"HF_ACCOUNT/gemma-finetune-gguf\",\n", " token = \"hf_...\",\n", " )" ] @@ -1335,9 +1343,10 @@ " \n", " \n", "\n", - " Join Discord if you need help + \u2b50\ufe0f Star us on Github \u2b50\ufe0f\n", + " Join Discord if you need help + ⭐️ Star us on Github ⭐️\n", "\n", - "\n This notebook and all Unsloth notebooks are licensed [LGPL-3.0](https://github.com/unslothai/notebooks?tab=LGPL-3.0-1-ov-file#readme).\n" + "\n", + " This notebook and all Unsloth notebooks are licensed [LGPL-3.0](https://github.com/unslothai/notebooks?tab=LGPL-3.0-1-ov-file#readme).\n" ] } ], @@ -1511,9 +1520,9 @@ "description": "", "description_tooltip": null, "layout": "IPY_MODEL_3530e2b431c041c6aeeaca4808ba0424", - 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"placeholder": "\u200b", + "placeholder": "​", "style": "IPY_MODEL_3a24c19f9a6a4e4dba162062a0562db2", - "value": "\u2007100000/100000\u2007[00:07<00:00,\u200713546.66\u2007examples/s]" + "value": " 100000/100000 [00:07<00:00, 13546.66 examples/s]" } }, "ea9045a5c4504a5e96e6a7b13767fe4e": { @@ -6819,9 +6828,9 @@ "description": "", "description_tooltip": null, "layout": "IPY_MODEL_28063728d31f45aea5beffd3f114eec7", - "placeholder": "\u200b", + "placeholder": "​", "style": "IPY_MODEL_d86e65b9ea5f47c58b3f2274e4989f93", - "value": "Generating\u2007train\u2007split:\u2007100%" + "value": "Generating train split: 100%" } }, "efa41d07d0fa4adda8025fe9490ed850": { @@ -6975,9 +6984,9 @@ "description": "", "description_tooltip": null, "layout": "IPY_MODEL_28de62814a6847e0a0b41ec6bf8fdc66", - "placeholder": "\u200b", + "placeholder": "​", "style": "IPY_MODEL_c43cef665c9542f982986a74dc50ca98", - "value": "Map\u2007(num_proc=2):\u2007100%" + "value": "Map (num_proc=2): 100%" } }, "f89c08592a25432497bb312f58a13c5c": { @@ -7085,9 +7094,9 @@ "description": "", "description_tooltip": null, "layout": "IPY_MODEL_a0cf0f8dd74a4d5181d465fa7ff52915", - "placeholder": "\u200b", + "placeholder": "​", "style": "IPY_MODEL_529996f48ccf404584725386d33401f9", - "value": "Map:\u2007100%" + "value": "Map: 100%" } }, "fab7a02d350946ae9563a05cfd04e22b": { @@ -7187,4 +7196,4 @@ }, "nbformat": 4, "nbformat_minor": 4 -} \ No newline at end of file +} diff --git a/original_template/Gemma3N_(4B)-Audio.ipynb b/original_template/Gemma3N_(4B)-Audio.ipynb index 5e47335d..b9599eca 100644 --- a/original_template/Gemma3N_(4B)-Audio.ipynb +++ b/original_template/Gemma3N_(4B)-Audio.ipynb @@ -1618,10 +1618,9 @@ "source": [ "if False: # Change to True to upload GGUF\n", " model.push_to_hub_gguf(\n", - " \"gemma-3N-finetune\",\n", + " \"HF_ACCOUNT/gemma-3N-finetune-gguf\",\n", " processor,\n", " quantization_method = \"Q8_0\", # Only Q8_0, BF16, F16 supported\n", - " repo_id = \"HF_ACCOUNT/gemma-3N-finetune-gguf\",\n", " token = \"hf_...\",\n", " )" ] diff --git a/original_template/Gemma3N_(4B)-Conversational.ipynb b/original_template/Gemma3N_(4B)-Conversational.ipynb index d66b1856..6b5dc08a 100644 --- a/original_template/Gemma3N_(4B)-Conversational.ipynb +++ b/original_template/Gemma3N_(4B)-Conversational.ipynb @@ -2012,10 +2012,9 @@ "source": [ "if False: # Change to True to upload GGUF\n", " model.push_to_hub_gguf(\n", - " \"gemma-3N-finetune\",\n", + " \"HF_ACCOUNT/gemma-3N-finetune-gguf\",\n", " tokenizer,\n", " quantization_method = \"Q8_0\", # Only Q8_0, BF16, F16 supported\n", - " repo_id = \"HF_ACCOUNT/gemma-3N-finetune-gguf\",\n", " token = \"hf_...\",\n", " )" ] diff --git a/original_template/Gemma3_(1B)-GRPO.ipynb b/original_template/Gemma3_(1B)-GRPO.ipynb index daa20e9d..ee0615ba 100644 --- a/original_template/Gemma3_(1B)-GRPO.ipynb +++ b/original_template/Gemma3_(1B)-GRPO.ipynb @@ -1908,10 +1908,9 @@ "source": [ "if False: # Change to True to upload GGUF\n", " model.push_to_hub_gguf(\n", - " \"gemma-3-finetune\",\n", + " \"HF_ACCOUNT/gemma-finetune-gguf\",\n", " tokenizer,\n", " quantization_method = \"Q8_0\", # Only Q8_0, BF16, F16 supported\n", - " repo_id = \"HF_ACCOUNT/gemma-finetune-gguf\",\n", " token = \"hf_...\",\n", " )" ] diff --git a/original_template/Gemma3_(270M).ipynb b/original_template/Gemma3_(270M).ipynb index 64c93913..7f695105 100644 --- a/original_template/Gemma3_(270M).ipynb +++ b/original_template/Gemma3_(270M).ipynb @@ -1700,7 +1700,7 @@ }, { "cell_type": "code", - "execution_count": 22, + "execution_count": null, "metadata": { "id": "S-TqCnZVu5Ll" }, @@ -1708,10 +1708,9 @@ "source": [ "if False: # Change to True to upload GGUF\n", " model.push_to_hub_gguf(\n", - " \"gemma-3-finetune\",\n", + " \"HF_ACCOUNT/gemma-finetune-gguf\",\n", " tokenizer,\n", " quantization_method = \"Q8_0\", # Only Q8_0, BF16, F16 supported\n", - " repo_id = \"HF_ACCOUNT/gemma-finetune-gguf\",\n", " token = \"hf_...\",\n", " )" ] diff --git a/original_template/Gemma3_(27B)_A100-Conversational.ipynb b/original_template/Gemma3_(27B)_A100-Conversational.ipynb index 1d72453c..f2b20c28 100644 --- a/original_template/Gemma3_(27B)_A100-Conversational.ipynb +++ b/original_template/Gemma3_(27B)_A100-Conversational.ipynb @@ -1057,10 +1057,9 @@ "source": [ "if False: # Change to True to upload GGUF\n", " model.push_to_hub_gguf(\n", - " \"gemma-3-finetune\",\n", + " \"HF_ACCOUNT/gemma-finetune-gguf\",\n", " tokenizer,\n", " quantization_method = \"Q8_0\", # Only Q8_0, BF16, F16 supported\n", - " repo_id = \"HF_ACCOUNT/gemma-finetune-gguf\",\n", " token = \"hf_...\",\n", " )" ] diff --git a/original_template/Gemma3_(4B).ipynb b/original_template/Gemma3_(4B).ipynb index 2e454036..6945bc6e 100644 --- a/original_template/Gemma3_(4B).ipynb +++ b/original_template/Gemma3_(4B).ipynb @@ -1285,10 +1285,9 @@ "source": [ "if False: # Change to True to upload GGUF\n", " model.push_to_hub_gguf(\n", - " \"gemma-3-finetune\",\n", + " \"gHF_ACCOUNT/gemma-finetune-gguf\",\n", " tokenizer,\n", " quantization_method = \"Q8_0\", # Only Q8_0, BF16, F16 supported\n", - " repo_id = \"HF_ACCOUNT/gemma-finetune-gguf\",\n", " token = \"hf_...\",\n", " )" ] diff --git a/python_scripts/Gemma3N_(4B)-Audio.py b/python_scripts/Gemma3N_(4B)-Audio.py index 1ef6546f..3c622ca8 100644 --- a/python_scripts/Gemma3N_(4B)-Audio.py +++ b/python_scripts/Gemma3N_(4B)-Audio.py @@ -491,10 +491,9 @@ def collate_fn(examples): if False: # Change to True to upload GGUF model.push_to_hub_gguf( - "gemma-3N-finetune", + "HF_ACCOUNT/gemma-3N-finetune-gguf", processor, quantization_method = "Q8_0", # Only Q8_0, BF16, F16 supported - repo_id = "HF_ACCOUNT/gemma-3N-finetune-gguf", token = "hf_...", ) diff --git a/python_scripts/Gemma3N_(4B)-Conversational.py b/python_scripts/Gemma3N_(4B)-Conversational.py index 3928e2a1..342203a3 100644 --- a/python_scripts/Gemma3N_(4B)-Conversational.py +++ b/python_scripts/Gemma3N_(4B)-Conversational.py @@ -529,10 +529,9 @@ def formatting_prompts_func(examples): if False: # Change to True to upload GGUF model.push_to_hub_gguf( - "gemma-3N-finetune", + "HF_ACCOUNT/gemma-3N-finetune-gguf", tokenizer, quantization_method = "Q8_0", # Only Q8_0, BF16, F16 supported - repo_id = "HF_ACCOUNT/gemma-3N-finetune-gguf", token = "hf_...", ) diff --git a/python_scripts/Gemma3_(1B)-GRPO.py b/python_scripts/Gemma3_(1B)-GRPO.py index b39f6b7b..b67873dc 100644 --- a/python_scripts/Gemma3_(1B)-GRPO.py +++ b/python_scripts/Gemma3_(1B)-GRPO.py @@ -479,10 +479,9 @@ def check_numbers(prompts, completions, answer, **kwargs): if False: # Change to True to upload GGUF model.push_to_hub_gguf( - "gemma-3-finetune", + "HF_ACCOUNT/gemma-finetune-gguf", tokenizer, quantization_method = "Q8_0", # Only Q8_0, BF16, F16 supported - repo_id = "HF_ACCOUNT/gemma-finetune-gguf", token = "hf_...", ) diff --git a/python_scripts/Gemma3_(270M).py b/python_scripts/Gemma3_(270M).py index 9d470be4..11614d8d 100644 --- a/python_scripts/Gemma3_(270M).py +++ b/python_scripts/Gemma3_(270M).py @@ -372,10 +372,9 @@ def formatting_prompts_func(examples): if False: # Change to True to upload GGUF model.push_to_hub_gguf( - "gemma-3-finetune", + "HF_ACCOUNT/gemma-finetune-gguf", tokenizer, quantization_method = "Q8_0", # Only Q8_0, BF16, F16 supported - repo_id = "HF_ACCOUNT/gemma-finetune-gguf", token = "hf_...", ) diff --git a/python_scripts/Gemma3_(27B)_A100-Conversational.py b/python_scripts/Gemma3_(27B)_A100-Conversational.py index dbcc39c1..f0f7dd76 100644 --- a/python_scripts/Gemma3_(27B)_A100-Conversational.py +++ b/python_scripts/Gemma3_(27B)_A100-Conversational.py @@ -411,10 +411,9 @@ def formatting_prompts_func(examples): if False: # Change to True to upload GGUF model.push_to_hub_gguf( - "gemma-3-finetune", + "HF_ACCOUNT/gemma-finetune-gguf", tokenizer, quantization_method = "Q8_0", # Only Q8_0, BF16, F16 supported - repo_id = "HF_ACCOUNT/gemma-finetune-gguf", token = "hf_...", ) diff --git a/python_scripts/Gemma3_(4B).py b/python_scripts/Gemma3_(4B).py index 7c92709f..c5eb7169 100644 --- a/python_scripts/Gemma3_(4B).py +++ b/python_scripts/Gemma3_(4B).py @@ -411,10 +411,9 @@ def formatting_prompts_func(examples): if False: # Change to True to upload GGUF model.push_to_hub_gguf( - "gemma-3-finetune", + "HF_ACCOUNT/gemma-finetune-gguf", tokenizer, quantization_method = "Q8_0", # Only Q8_0, BF16, F16 supported - repo_id = "HF_ACCOUNT/gemma-finetune-gguf", token = "hf_...", ) diff --git a/python_scripts/HuggingFace Course-Gemma3_(1B)-GRPO.py b/python_scripts/HuggingFace Course-Gemma3_(1B)-GRPO.py index 1814f842..d99f852f 100644 --- a/python_scripts/HuggingFace Course-Gemma3_(1B)-GRPO.py +++ b/python_scripts/HuggingFace Course-Gemma3_(1B)-GRPO.py @@ -481,10 +481,9 @@ def check_numbers(prompts, completions, answer, **kwargs): if False: # Change to True to upload GGUF model.push_to_hub_gguf( - "gemma-3-finetune", + "HF_ACCOUNT/gemma-finetune-gguf", tokenizer, quantization_method = "Q8_0", # Only Q8_0, BF16, F16 supported - repo_id = "HF_ACCOUNT/gemma-finetune-gguf", token = "hf_...", ) diff --git a/python_scripts/Kaggle-Gemma3N_(4B)-Audio.py b/python_scripts/Kaggle-Gemma3N_(4B)-Audio.py index 6b0371b7..fb82b251 100644 --- a/python_scripts/Kaggle-Gemma3N_(4B)-Audio.py +++ b/python_scripts/Kaggle-Gemma3N_(4B)-Audio.py @@ -491,10 +491,9 @@ def collate_fn(examples): if False: # Change to True to upload GGUF model.push_to_hub_gguf( - "gemma-3N-finetune", + "HF_ACCOUNT/gemma-3N-finetune-gguf", processor, quantization_method = "Q8_0", # Only Q8_0, BF16, F16 supported - repo_id = "HF_ACCOUNT/gemma-3N-finetune-gguf", token = "hf_...", ) diff --git a/python_scripts/Kaggle-Gemma3N_(4B)-Conversational.py b/python_scripts/Kaggle-Gemma3N_(4B)-Conversational.py index ad9510c7..4211b579 100644 --- a/python_scripts/Kaggle-Gemma3N_(4B)-Conversational.py +++ b/python_scripts/Kaggle-Gemma3N_(4B)-Conversational.py @@ -529,10 +529,9 @@ def formatting_prompts_func(examples): if False: # Change to True to upload GGUF model.push_to_hub_gguf( - "gemma-3N-finetune", + "HF_ACCOUNT/gemma-3N-finetune-gguf", tokenizer, quantization_method = "Q8_0", # Only Q8_0, BF16, F16 supported - repo_id = "HF_ACCOUNT/gemma-3N-finetune-gguf", token = "hf_...", ) diff --git a/python_scripts/Kaggle-Gemma3_(1B)-GRPO.py b/python_scripts/Kaggle-Gemma3_(1B)-GRPO.py index 652d373f..c27a4e67 100644 --- a/python_scripts/Kaggle-Gemma3_(1B)-GRPO.py +++ b/python_scripts/Kaggle-Gemma3_(1B)-GRPO.py @@ -457,10 +457,9 @@ def check_numbers(prompts, completions, answer, **kwargs): if False: # Change to True to upload GGUF model.push_to_hub_gguf( - "gemma-3-finetune", + "HF_ACCOUNT/gemma-finetune-gguf", tokenizer, quantization_method = "Q8_0", # Only Q8_0, BF16, F16 supported - repo_id = "HF_ACCOUNT/gemma-finetune-gguf", token = "hf_...", ) diff --git a/python_scripts/Kaggle-Gemma3_(270M).py b/python_scripts/Kaggle-Gemma3_(270M).py index a8b08ced..077292e5 100644 --- a/python_scripts/Kaggle-Gemma3_(270M).py +++ b/python_scripts/Kaggle-Gemma3_(270M).py @@ -372,10 +372,9 @@ def formatting_prompts_func(examples): if False: # Change to True to upload GGUF model.push_to_hub_gguf( - "gemma-3-finetune", + "HF_ACCOUNT/gemma-finetune-gguf", tokenizer, quantization_method = "Q8_0", # Only Q8_0, BF16, F16 supported - repo_id = "HF_ACCOUNT/gemma-finetune-gguf", token = "hf_...", ) diff --git a/python_scripts/Kaggle-Gemma3_(27B)_A100-Conversational.py b/python_scripts/Kaggle-Gemma3_(27B)_A100-Conversational.py index 44bfab05..96a49c9a 100644 --- a/python_scripts/Kaggle-Gemma3_(27B)_A100-Conversational.py +++ b/python_scripts/Kaggle-Gemma3_(27B)_A100-Conversational.py @@ -411,10 +411,9 @@ def formatting_prompts_func(examples): if False: # Change to True to upload GGUF model.push_to_hub_gguf( - "gemma-3-finetune", + "HF_ACCOUNT/gemma-finetune-gguf", tokenizer, quantization_method = "Q8_0", # Only Q8_0, BF16, F16 supported - repo_id = "HF_ACCOUNT/gemma-finetune-gguf", token = "hf_...", ) diff --git a/python_scripts/Kaggle-Gemma3_(4B).py b/python_scripts/Kaggle-Gemma3_(4B).py index 972e6b9c..444e9556 100644 --- a/python_scripts/Kaggle-Gemma3_(4B).py +++ b/python_scripts/Kaggle-Gemma3_(4B).py @@ -411,10 +411,9 @@ def formatting_prompts_func(examples): if False: # Change to True to upload GGUF model.push_to_hub_gguf( - "gemma-3-finetune", + "HF_ACCOUNT/gemma-finetune-gguf", tokenizer, quantization_method = "Q8_0", # Only Q8_0, BF16, F16 supported - repo_id = "HF_ACCOUNT/gemma-finetune-gguf", token = "hf_...", ) From a0671d8af1f0fb8b5b4e2933e99dbc2f7b4b8e40 Mon Sep 17 00:00:00 2001 From: "Farjana Kabir (Samanta)" Date: Sun, 9 Nov 2025 09:44:53 +0600 Subject: [PATCH 2/3] Update original_template/Gemma3_(4B).ipynb Co-authored-by: gemini-code-assist[bot] <176961590+gemini-code-assist[bot]@users.noreply.github.com> --- original_template/Gemma3_(4B).ipynb | 3 ++- 1 file changed, 2 insertions(+), 1 deletion(-) diff --git a/original_template/Gemma3_(4B).ipynb b/original_template/Gemma3_(4B).ipynb index 6945bc6e..5235506e 100644 --- a/original_template/Gemma3_(4B).ipynb +++ b/original_template/Gemma3_(4B).ipynb @@ -1285,7 +1285,8 @@ "source": [ "if False: # Change to True to upload GGUF\n", " model.push_to_hub_gguf(\n", - " \"gHF_ACCOUNT/gemma-finetune-gguf\",\n", + "HF_ACCOUNT/gemma-finetune-gguf", + " tokenizer,\n", " quantization_method = \"Q8_0\", # Only Q8_0, BF16, F16 supported\n", " token = \"hf_...\",\n", From 2f2b501f6e289917cea3d760ebfe40a1d1847810 Mon Sep 17 00:00:00 2001 From: "Farjana Kabir (Samanta)" Date: Sun, 9 Nov 2025 09:54:53 +0600 Subject: [PATCH 3/3] Fix formatting of model push to hub GGUF code --- original_template/Gemma3_(4B).ipynb | 3 +-- 1 file changed, 1 insertion(+), 2 deletions(-) diff --git a/original_template/Gemma3_(4B).ipynb b/original_template/Gemma3_(4B).ipynb index 5235506e..b0443b69 100644 --- a/original_template/Gemma3_(4B).ipynb +++ b/original_template/Gemma3_(4B).ipynb @@ -1285,8 +1285,7 @@ "source": [ "if False: # Change to True to upload GGUF\n", " model.push_to_hub_gguf(\n", - "HF_ACCOUNT/gemma-finetune-gguf", - + " \"HF_ACCOUNT/gemma-finetune-gguf\",\n", " tokenizer,\n", " quantization_method = \"Q8_0\", # Only Q8_0, BF16, F16 supported\n", " token = \"hf_...\",\n",