chore(model gallery): 🤖 add 1 new models via gallery agent

gallery/index.yaml

@@ -3295,7 +3295,7 @@
     - gemma3
     - gemma-3
   overrides:
     #mmproj: gemma-3-27b-it-mmproj-f16.gguf
     parameters:
       model: gemma-3-27b-it-Q4_K_M.gguf
   files:
@@ -3313,7 +3313,7 @@
   description: |
     google/gemma-3-12b-it is an open-source, state-of-the-art, lightweight, multimodal model built from the same research and technology used to create the Gemini models. It is capable of handling text and image input and generating text output. It has a large context window of 128K tokens and supports over 140 languages. The 12B variant has been fine-tuned using the instruction-tuning approach. Gemma 3 models are suitable for a variety of text generation and image understanding tasks, including question answering, summarization, and reasoning. Their relatively small size makes them deployable in environments with limited resources such as laptops, desktops, or your own cloud infrastructure.
   overrides:
     #mmproj: gemma-3-12b-it-mmproj-f16.gguf
     parameters:
       model: gemma-3-12b-it-Q4_K_M.gguf
   files:
@@ -3331,7 +3331,7 @@
   description: |
     Gemma is a family of lightweight, state-of-the-art open models from Google, built from the same research and technology used to create the Gemini models. Gemma 3 models are multimodal, handling text and image input and generating text output, with open weights for both pre-trained variants and instruction-tuned variants. Gemma 3 has a large, 128K context window, multilingual support in over 140 languages, and is available in more sizes than previous versions. Gemma 3 models are well-suited for a variety of text generation and image understanding tasks, including question answering, summarization, and reasoning. Their relatively small size makes it possible to deploy them in environments with limited resources such as laptops, desktops or your own cloud infrastructure, democratizing access to state of the art AI models and helping foster innovation for everyone. Gemma-3-4b-it is a 4 billion parameter model.
   overrides:
     #mmproj: gemma-3-4b-it-mmproj-f16.gguf
     parameters:
       model: gemma-3-4b-it-Q4_K_M.gguf
   files:
@@ -6949,7 +6949,7 @@
       sha256: 2756551de7d8ff7093c2c5eec1cd00f1868bc128433af53f5a8d434091d4eb5a
       uri: huggingface://Triangle104/Nano_Imp_1B-Q8_0-GGUF/nano_imp_1b-q8_0.gguf
 - &qwen25
   name: "qwen2.5-14b-instruct" ## Qwen2.5
   icon: https://avatars.githubusercontent.com/u/141221163
   url: "github:mudler/LocalAI/gallery/chatml.yaml@master"
   license: apache-2.0
@@ -23203,3 +23203,42 @@
     - filename: Spiral-Qwen3-4B-Multi-Env.Q4_K_M.gguf
       sha256: e91914c18cb91f2a3ef96d8e62a18b595dd6c24fad901dea639e714bc7443b09
       uri: huggingface://mradermacher/Spiral-Qwen3-4B-Multi-Env-GGUF/Spiral-Qwen3-4B-Multi-Env.Q4_K_M.gguf
+- !!merge <<: *gptoss
+  name: "metatune-gpt20b-r1.1-i1"
+  urls:
+    - https://huggingface.co/mradermacher/metatune-gpt20b-R1.1-i1-GGUF
+  description: |
+    **Model Name:** MetaTune-GPT20B-R1.1
+    **Base Model:** unsloth/gpt-oss-20b-unsloth-bnb-4bit
+    **Repository:** [EpistemeAI/metatune-gpt20b-R1.1](https://huggingface.co/EpistemeAI/metatune-gpt20b-R1.1)
+    **License:** Apache 2.0
+
+    **Description:**
+    MetaTune-GPT20B-R1.1 is a large language model fine-tuned for recursive self-improvement, making it one of the first publicly released models capable of autonomously generating training data, evaluating its own performance, and adjusting its hyperparameters to improve over time. Built upon the open-weight GPT-OSS 20B architecture and trained with Unsloth's optimized 4-bit quantization, this model excels in complex reasoning, agentic tasks, and function calling. It supports tools like web browsing and structured output generation, and is particularly effective in high-reasoning use cases such as scientific problem-solving and math reasoning.
+
+    **Performance Highlights (Zero-shot):**
+    - **GPQA Diamond:** 93.3% exact match
+    - **GSM8K (Chain-of-Thought):** 100% exact match
+
+    **Recommended Use:**
+    - Advanced reasoning & planning
+    - Autonomous agent workflows
+    - Research, education, and technical problem-solving
+
+    **Safety Note:**
+    Use with caution. For safety-critical applications, pair with a safety guardrail model such as [openai/gpt-oss-safeguard-20b](https://huggingface.co/openai/gpt-oss-safeguard-20b).
+
+    **Fine-Tuned From:** unsloth/gpt-oss-20b-unsloth-bnb-4bit
+    **Training Method:** Recursive Self-Improvement on the [Recursive Self-Improvement Dataset](https://huggingface.co/datasets/EpistemeAI/recursive_self_improvement_dataset)
+    **Framework:** Hugging Face TRL + Unsloth for fast, efficient training
+
+    **Inference Tip:** Set reasoning level to "high" for best results and to reduce prompt injection risks.
+
+    👉 [View on Hugging Face](https://huggingface.co/EpistemeAI/metatune-gpt20b-R1.1) | [GitHub: Recursive Self-Improvement](https://github.com/openai/harmony)
+  overrides:
+    parameters:
+      model: metatune-gpt20b-R1.1.i1-Q4_K_M.gguf
+  files:
+    - filename: metatune-gpt20b-R1.1.i1-Q4_K_M.gguf
+      sha256: 82a77f5681c917df6375bc0b6c28bf2800d1731e659fd9bbde7b5598cf5e9d0a
+      uri: huggingface://mradermacher/metatune-gpt20b-R1.1-i1-GGUF/metatune-gpt20b-R1.1.i1-Q4_K_M.gguf