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)"
      ],
      "metadata": {
        "id": "oBCcFzqw1twn"
      }
    },
    {
      "cell_type": "code",
      "execution_count": 1,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "k3vHA0mPHadK",
        "outputId": "f6515b83-2d67-4508-ba63-c7c6d6ecffce"
      },
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Tue Mar 14 20:35:18 2023       \n",
            "+-----------------------------------------------------------------------------+\n",
            "| NVIDIA-SMI 525.85.12    Driver Version: 525.85.12    CUDA Version: 12.0     |\n",
            "|-------------------------------+----------------------+----------------------+\n",
            "| GPU  Name        Persistence-M| Bus-Id        Disp.A | Volatile Uncorr. ECC |\n",
            "| Fan  Temp  Perf  Pwr:Usage/Cap|         Memory-Usage | GPU-Util  Compute M. |\n",
            "|                               |                      |               MIG M. |\n",
            "|===============================+======================+======================|\n",
            "|   0  Tesla T4            Off  | 00000000:00:04.0 Off |                    0 |\n",
            "| N/A   56C    P0    27W /  70W |      0MiB / 15360MiB |      0%      Default |\n",
            "|                               |                      |                  N/A |\n",
            "+-------------------------------+----------------------+----------------------+\n",
            "                                                                               \n",
            "+-----------------------------------------------------------------------------+\n",
            "| Processes:                                                                  |\n",
            "|  GPU   GI   CI        PID   Type   Process name                  GPU Memory |\n",
            "|        ID   ID                                                   Usage      |\n",
            "|=============================================================================|\n",
            "|  No running processes found                                                 |\n",
            "+-----------------------------------------------------------------------------+\n"
          ]
        }
      ],
      "source": [
        "!nvidia-smi"
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "!pip install --upgrade git+https://github.com/huggingface/diffusers.git transformers accelerate scipy xformers gradio -q"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "d11zAb6iHfF0",
        "outputId": "bc6af92b-18a8-4780-edd9-58b21bad3ff8"
      },
      "execution_count": 2,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "  Installing build dependencies ... \u001b[?25l\u001b[?25hdone\n",
            "  Getting requirements to build wheel ... \u001b[?25l\u001b[?25hdone\n",
            "  Preparing metadata (pyproject.toml) ... \u001b[?25l\u001b[?25hdone\n",
            "\u001b[2K     \u001b[90m━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[32m6.3/6.3 MB\u001b[0m \u001b[31m40.5 MB/s\u001b[0m eta \u001b[36m0:00:00\u001b[0m\n",
            "\u001b[2K     \u001b[90m━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[32m212.8/212.8 KB\u001b[0m \u001b[31m18.4 MB/s\u001b[0m eta \u001b[36m0:00:00\u001b[0m\n",
            "\u001b[2K     \u001b[90m━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[32m50.9/50.9 MB\u001b[0m \u001b[31m10.6 MB/s\u001b[0m eta \u001b[36m0:00:00\u001b[0m\n",
            "\u001b[2K     \u001b[90m━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[32m15.8/15.8 MB\u001b[0m \u001b[31m44.2 MB/s\u001b[0m eta \u001b[36m0:00:00\u001b[0m\n",
            "\u001b[2K     \u001b[90m━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[32m199.2/199.2 KB\u001b[0m \u001b[31m16.3 MB/s\u001b[0m eta \u001b[36m0:00:00\u001b[0m\n",
            "\u001b[2K     \u001b[90m━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[32m7.6/7.6 MB\u001b[0m \u001b[31m103.1 MB/s\u001b[0m eta \u001b[36m0:00:00\u001b[0m\n",
            "\u001b[2K     \u001b[90m━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[32m140.9/140.9 KB\u001b[0m \u001b[31m17.3 MB/s\u001b[0m eta \u001b[36m0:00:00\u001b[0m\n",
            "\u001b[2K     \u001b[90m━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[32m1.0/1.0 MB\u001b[0m \u001b[31m69.2 MB/s\u001b[0m eta \u001b[36m0:00:00\u001b[0m\n",
            "\u001b[2K     \u001b[90m━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[32m84.5/84.5 KB\u001b[0m \u001b[31m8.8 MB/s\u001b[0m eta \u001b[36m0:00:00\u001b[0m\n",
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            "\u001b[?25h  Preparing metadata (setup.py) ... \u001b[?25l\u001b[?25hdone\n",
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            "\u001b[2K     \u001b[90m━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[32m58.3/58.3 KB\u001b[0m \u001b[31m7.7 MB/s\u001b[0m eta \u001b[36m0:00:00\u001b[0m\n",
            "\u001b[2K     \u001b[90m━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[32m80.6/80.6 KB\u001b[0m \u001b[31m10.5 MB/s\u001b[0m eta \u001b[36m0:00:00\u001b[0m\n",
            "\u001b[?25h  Building wheel for diffusers (pyproject.toml) ... \u001b[?25l\u001b[?25hdone\n",
            "  Building wheel for ffmpy (setup.py) ... \u001b[?25l\u001b[?25hdone\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "from diffusers import StableDiffusionPipeline, EulerDiscreteScheduler\n",
        "import torch"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "f72ZkqwMHfI4",
        "outputId": "8378fd90-45a0-4afe-9ff6-f86cf2ccacb5"
      },
      "execution_count": 3,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stderr",
          "text": [
            "WARNING:xformers:A matching Triton is not available, some optimizations will not be enabled.\n",
            "Error caught was: No module named 'triton'\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "model_id = \"stabilityai/stable-diffusion-2\"\n",
        "scheduler = EulerDiscreteScheduler.from_pretrained(model_id, subfolder=\"scheduler\")\n",
        "pipe = StableDiffusionPipeline.from_pretrained(model_id, scheduler=scheduler, revision=\"fp16\", torch_dtype=torch.float16)\n",
        "pipe = pipe.to(\"cuda\")"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 433,
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        "id": "5C1Y-fGRHfLp",
        "outputId": "88e981ff-218f-4192-e3c8-7c386be39a8c"
      },
      "execution_count": 4,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
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            }
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          "metadata": {}
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            }
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            }
          },
          "metadata": {}
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    {
      "cell_type": "code",
      "source": [
        "def text2iamge(prompt):\n",
        "\n",
        "  image = pipe(prompt, height=768, width=768, guidance_scale = 10).images[0] \n",
        "  image.save(\"sd_image.png\")\n",
        "  return image"
      ],
      "metadata": {
        "id": "qKpJ6kQBHfRe"
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      "execution_count": 5,
      "outputs": []
    },
    {
      "cell_type": "code",
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        "prompt = \"3d cartoon of a cat singing\""
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      "metadata": {
        "id": "oPY2TT3DHfOq"
      },
      "execution_count": 6,
      "outputs": []
    },
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      "metadata": {
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      },
      "execution_count": 8,
      "outputs": []
    },
    {
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          "text": [
            "Colab notebook detected. This cell will run indefinitely so that you can see errors and logs. To turn off, set debug=False in launch().\n",
            "Running on public URL: https://e9a9579398775fc46e.gradio.live\n",
            "\n",
            "This share link expires in 72 hours. For free permanent hosting and GPU upgrades (NEW!), check out Spaces: https://huggingface.co/spaces\n"
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