Gradio_ML_Sharing_Models_building_demos.ipynb

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      "metadata": {
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        "<a href=\"https://colab.research.google.com/github/SACHINSIROHI47/DataScience_with_Python_Programming_Project/blob/main/Gradio_ML_Sharing_Models_building_demos.ipynb\" target=\"_parent\"><img src=\"https://colab.research.google.com/assets/colab-badge.svg\" alt=\"Open In Colab\"/></a>"
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "!pip install gradio"
      ],
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        "id": "_wII74UVCQOA",
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        },
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      },
      "execution_count": 2,
      "outputs": [
        {
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          "name": "stdout",
          "text": [
            "Collecting gradio\n",
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            "\u001b[?25hInstalling collected packages: pydub, websockets, uvicorn, tomlkit, semantic-version, ruff, python-multipart, markupsafe, ffmpy, aiofiles, starlette, huggingface-hub, safehttpx, gradio-client, fastapi, gradio\n",
            "  Attempting uninstall: markupsafe\n",
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            "      Successfully uninstalled huggingface-hub-0.24.7\n",
            "Successfully installed aiofiles-23.2.1 fastapi-0.115.4 ffmpy-0.4.0 gradio-5.5.0 gradio-client-1.4.2 huggingface-hub-0.26.2 markupsafe-2.1.5 pydub-0.25.1 python-multipart-0.0.12 ruff-0.7.3 safehttpx-0.1.1 semantic-version-2.10.0 starlette-0.41.2 tomlkit-0.12.0 uvicorn-0.32.0 websockets-12.0\n"
          ]
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      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 645
        },
        "id": "2PHre8v7_DHk",
        "outputId": "b3582723-cc0e-4d02-b463-7a9637987cc7"
      },
      "outputs": [
        {
          "metadata": {
            "tags": null
          },
          "name": "stdout",
          "output_type": "stream",
          "text": [
            "Running Gradio in a Colab notebook requires sharing enabled. Automatically setting `share=True` (you can turn this off by setting `share=False` in `launch()` explicitly).\n",
            "\n",
            "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://c91ee97720815ee742.gradio.live\n",
            "\n",
            "This share link expires in 72 hours. For free permanent hosting and GPU upgrades, run `gradio deploy` from the terminal in the working directory to deploy to Hugging Face Spaces (https://huggingface.co/spaces)\n"
          ]
        },
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      ],
      "source": [
        "import gradio as gr\n",
        "\n",
        "def greet(name,add, intensity):\n",
        "    return \"Hello, \" + name + \", Are you form \"+add+ \"!\" * int(intensity)\n",
        "\n",
        "demo = gr.Interface(\n",
        "    fn=greet,\n",
        "    inputs=[\"text\",\"text\", \"slider\"],\n",
        "    outputs=[\"text\"],\n",
        ")\n",
        "\n",
        "#set debug true\n",
        "demo.launch(debug=True)\n"
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "!pip install gradio torch diffusers transformers"
      ],
      "metadata": {
        "id": "JQweBbCkCUp9"
      },
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "import gradio as gr\n",
        "import torch\n",
        "from diffusers import StableDiffusionPipeline\n",
        "\n",
        "# Load the Stable Diffusion model (preferably on GPU if available)\n",
        "model_id = \"CompVis/stable-diffusion-v1-4\"\n",
        "pipe = StableDiffusionPipeline.from_pretrained(model_id, torch_dtype=torch.float16)\n",
        "pipe = pipe.to(\"cuda\" if torch.cuda.is_available() else \"cpu\")\n",
        "\n",
        "# Function to generate images based on text prompts\n",
        "def generate_image(prompt):\n",
        "    with torch.no_grad():\n",
        "        # Generate image based on the prompt\n",
        "        image = pipe(prompt).images[0]\n",
        "    return image\n",
        "\n",
        "# Gradio Interface\n",
        "interface = gr.Interface(\n",
        "    fn=generate_image,\n",
        "    inputs=gr.Textbox(label=\"Enter your prompt\"),\n",
        "    outputs=gr.Image(label=\"Generated Image\"),\n",
        "    title=\"Stable Diffusion Image Generator\",\n",
        "    description=\"Generate images based on a text prompt using Stable Diffusion.\"\n",
        ")\n",
        "\n",
        "# Launch the Gradio app\n",
        "interface.launch(debug=True)\n"
      ],
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        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 1000,
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        },
        "id": "Tl3N7qq3AW3J",
        "outputId": "5933b408-d678-4c40-dcc7-8a9fb85e2681"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stderr",
          "text": [
            "The cache for model files in Transformers v4.22.0 has been updated. Migrating your old cache. This is a one-time only operation. You can interrupt this and resume the migration later on by calling `transformers.utils.move_cache()`.\n"
          ]
        },
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "0it [00:00, ?it/s]"
            ],
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        {
          "output_type": "stream",
          "name": "stderr",
          "text": [
            "/usr/local/lib/python3.10/dist-packages/huggingface_hub/utils/_auth.py:94: UserWarning: \n",
            "The secret `HF_TOKEN` does not exist in your Colab secrets.\n",
            "To authenticate with the Hugging Face Hub, create a token in your settings tab (https://huggingface.co/settings/tokens), set it as secret in your Google Colab and restart your session.\n",
            "You will be able to reuse this secret in all of your notebooks.\n",
            "Please note that authentication is recommended but still optional to access public models or datasets.\n",
            "  warnings.warn(\n"
          ]
        },
        {
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          "text": [
            "/usr/local/lib/python3.10/dist-packages/transformers/tokenization_utils_base.py:1601: FutureWarning: `clean_up_tokenization_spaces` was not set. It will be set to `True` by default. This behavior will be depracted in transformers v4.45, and will be then set to `False` by default. For more details check this issue: https://github.com/huggingface/transformers/issues/31884\n",
            "  warnings.warn(\n",
            "Pipelines loaded with `dtype=torch.float16` cannot run with `cpu` device. It is not recommended to move them to `cpu` as running them will fail. Please make sure to use an accelerator to run the pipeline in inference, due to the lack of support for`float16` operations on this device in PyTorch. Please, remove the `torch_dtype=torch.float16` argument, or use another device for inference.\n",
            "Pipelines loaded with `dtype=torch.float16` cannot run with `cpu` device. It is not recommended to move them to `cpu` as running them will fail. Please make sure to use an accelerator to run the pipeline in inference, due to the lack of support for`float16` operations on this device in PyTorch. Please, remove the `torch_dtype=torch.float16` argument, or use another device for inference.\n",
            "Pipelines loaded with `dtype=torch.float16` cannot run with `cpu` device. It is not recommended to move them to `cpu` as running them will fail. Please make sure to use an accelerator to run the pipeline in inference, due to the lack of support for`float16` operations on this device in PyTorch. Please, remove the `torch_dtype=torch.float16` argument, or use another device for inference.\n",
            "Pipelines loaded with `dtype=torch.float16` cannot run with `cpu` device. It is not recommended to move them to `cpu` as running them will fail. Please make sure to use an accelerator to run the pipeline in inference, due to the lack of support for`float16` operations on this device in PyTorch. Please, remove the `torch_dtype=torch.float16` argument, or use another device for inference.\n"
          ]
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            "Running Gradio in a Colab notebook requires sharing enabled. Automatically setting `share=True` (you can turn this off by setting `share=False` in `launch()` explicitly).\n",
            "\n",
            "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://21f68689706028942d.gradio.live\n",
            "\n",
            "This share link expires in 72 hours. For free permanent hosting and GPU upgrades, run `gradio deploy` from the terminal in the working directory to deploy to Hugging Face Spaces (https://huggingface.co/spaces)\n"
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