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HF_Textual_Inversion.ipynb

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+{
+  "nbformat": 4,
+  "nbformat_minor": 0,
+  "metadata": {
+    "colab": {
+      "provenance": [],
+      "gpuType": "T4"
+    },
+    "kernelspec": {
+      "name": "python3",
+      "display_name": "Python 3"
+    },
+    "language_info": {
+      "name": "python"
+    },
+    "accelerator": "GPU"
+  },
+  "cells": [
+    {
+      "cell_type": "code",
+      "execution_count": 1,
+      "metadata": {
+        "colab": {
+          "base_uri": "https://localhost:8080/"
+        },
+        "id": "QV8xk7HmMX-M",
+        "outputId": "f92c1174-5e29-43fa-a54a-4dac3bfe6d59"
+      },
+      "outputs": [
+        {
+          "output_type": "stream",
+          "name": "stdout",
+          "text": [
+            "Cloning into 'diffusers'...\n",
+            "remote: Enumerating objects: 52829, done.\u001b[K\n",
+            "remote: Counting objects: 100% (1298/1298), done.\u001b[K\n",
+            "remote: Compressing objects: 100% (852/852), done.\u001b[K\n",
+            "remote: Total 52829 (delta 594), reused 966 (delta 418), pack-reused 51531\u001b[K\n",
+            "Receiving objects: 100% (52829/52829), 38.59 MiB | 24.11 MiB/s, done.\n",
+            "Resolving deltas: 100% (37517/37517), done.\n",
+            "/content/diffusers\n",
+            "  Installing build dependencies ... \u001b[?25l\u001b[?25hdone\n",
+            "  Checking if build backend supports build_editable ... \u001b[?25l\u001b[?25hdone\n",
+            "  Getting requirements to build editable ... \u001b[?25l\u001b[?25hdone\n",
+            "  Preparing editable metadata (pyproject.toml) ... \u001b[?25l\u001b[?25hdone\n",
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+            "\u001b[2K     \u001b[90m━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[32m54.5/54.5 kB\u001b[0m \u001b[31m7.9 MB/s\u001b[0m eta \u001b[36m0:00:00\u001b[0m\n",
+            "\u001b[2K     \u001b[90m━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[32m257.9/257.9 kB\u001b[0m \u001b[31m30.1 MB/s\u001b[0m eta \u001b[36m0:00:00\u001b[0m\n",
+            "\u001b[?25h  Building editable for diffusers (pyproject.toml) ... \u001b[?25l\u001b[?25hdone\n",
+            "\u001b[31mERROR: pip's dependency resolver does not currently take into account all the packages that are installed. This behaviour is the source of the following dependency conflicts.\n",
+            "ibis-framework 7.1.0 requires pyarrow<15,>=2, but you have pyarrow 15.0.0 which is incompatible.\u001b[0m\u001b[31m\n",
+            "\u001b[0m"
+          ]
+        }
+      ],
+      "source": [
+        "!git clone https://github.com/Bhavay-2001/diffusers\n",
+        "%cd diffusers\n",
+        "!pip install -q -e \".[dev]\""
+      ]
+    },
+    {
+      "cell_type": "code",
+      "source": [
+        "!pwd"
+      ],
+      "metadata": {
+        "colab": {
+          "base_uri": "https://localhost:8080/"
+        },
+        "id": "7tNQHp0MascO",
+        "outputId": "0ac02733-6a0f-484f-fd1b-ee58370e5bd8"
+      },
+      "execution_count": 2,
+      "outputs": [
+        {
+          "output_type": "stream",
+          "name": "stdout",
+          "text": [
+            "/content/diffusers\n"
+          ]
+        }
+      ]
+    },
+    {
+      "cell_type": "code",
+      "source": [
+        "import os\n",
+        "# /content/diffusers/src/diffusers/utils/hub_utils.py\n",
+        "from diffusers.src.diffusers.utils.hub_utils import load_or_create_model_card, populate_model_card"
+      ],
+      "metadata": {
+        "id": "kmQMzKuIXFvS"
+      },
+      "execution_count": 3,
+      "outputs": []
+    },
+    {
+      "cell_type": "code",
+      "source": [
+        "def save_model_card(repo_id: str, image_logs: dict =None, base_model: str=None, repo_folder: str=None):\n",
+        "    img_str = \"\"\n",
+        "    for i, log in enumerate(image_logs):\n",
+        "        images = log[\"images\"]\n",
+        "        validation_prompt = log[\"validation_prompt\"]\n",
+        "        validation_image = log[\"validation_image\"]\n",
+        "        validation_image.save(os.path.join(repo_folder, \"image_control.png\"))\n",
+        "        img_str += f\"![img_{i}](./image_{i}.png)\\n\"\n",
+        "\n",
+        "    model_description = f\"\"\"\n",
+        "    # Textual inversion text2image fine-tuning - {repo_id}\n",
+        "    These are textual inversion adaption weights for {base_model}. You can find some example images in the following. \\n\n",
+        "    {img_str}\n",
+        "    \"\"\"\n",
+        "\n",
+        "    model_card = load_or_create_model_card(\n",
+        "        repo_id_or_path=repo_id,\n",
+        "        from_training=True,\n",
+        "        license=\"creativeml-openrail-m\",\n",
+        "        base_model=base_model,\n",
+        "        model_description=model_description,\n",
+        "        inference=True,\n",
+        "    )\n",
+        "\n",
+        "    tags = [\"stable-diffusion-xl\", \"stable-diffusion-xl-diffusers\", \"text-to-image\", \"diffusers\", \"textual_inversion\"]\n",
+        "    model_card = populate_model_card(model_card, tags=tags)\n",
+        "\n",
+        "    model_card.save(os.path.join(repo_folder, \"README.md\"))"
+      ],
+      "metadata": {
+        "id": "LiA0ILIdVp91"
+      },
+      "execution_count": 4,
+      "outputs": []
+    },
+    {
+      "cell_type": "code",
+      "source": [
+        "from diffusers.src.diffusers.utils import load_image\n",
+        "\n",
+        "images = [\n",
+        "    load_image(\"https://huggingface.co/datasets/diffusers/docs-images/resolve/main/amused/A%20mushroom%20in%20%5BV%5D%20style.png\")\n",
+        "    for _ in range(3)\n",
+        "]\n",
+        "\n",
+        "image_logs = [\n",
+        "    dict(\n",
+        "        images=[image],\n",
+        "        validation_prompt=\"validation_prompt\",\n",
+        "        validation_image=image,\n",
+        "    )\n",
+        "    for image in images\n",
+        "]\n",
+        "\n",
+        "save_model_card(\n",
+        "    repo_id=\"Bhavay-2001/textual-inversion\",\n",
+        "    image_logs=image_logs,\n",
+        "    base_model=\"runwayml/stable-diffusion-v1-5\",\n",
+        "    repo_folder=\".\",\n",
+        ")"
+      ],
+      "metadata": {
+        "id": "5UN8yQmYXEYQ"
+      },
+      "execution_count": 5,
+      "outputs": []
+    },
+    {
+      "cell_type": "code",
+      "source": [
+        "!cat README.md"
+      ],
+      "metadata": {
+        "colab": {
+          "base_uri": "https://localhost:8080/"
+        },
+        "id": "yzaVaH8qfacW",
+        "outputId": "fed30f61-1e39-4d5d-93cf-c31e92bb5950"
+      },
+      "execution_count": 6,
+      "outputs": [
+        {
+          "output_type": "stream",
+          "name": "stdout",
+          "text": [
+            "---\n",
+            "license: creativeml-openrail-m\n",
+            "library_name: diffusers\n",
+            "tags:\n",
+            "- stable-diffusion-xl\n",
+            "- stable-diffusion-xl-diffusers\n",
+            "- text-to-image\n",
+            "- diffusers\n",
+            "- textual_inversion\n",
+            "inference: true\n",
+            "base_model: runwayml/stable-diffusion-v1-5\n",
+            "---\n",
+            "\n",
+            "<!-- This model card has been generated automatically according to the information the training script had access to. You\n",
+            "should probably proofread and complete it, then remove this comment. -->\n",
+            "\n",
+            "\n",
+            "    # Textual inversion text2image fine-tuning - Bhavay-2001/textual-inversion\n",
+            "    These are textual inversion adaption weights for runwayml/stable-diffusion-v1-5. You can find some example images in the following. \n",
+            "\n",
+            "    ![img_0](./image_0.png)\n",
+            "![img_1](./image_1.png)\n",
+            "![img_2](./image_2.png)\n",
+            "\n",
+            "    \n",
+            "\n",
+            "## Intended uses & limitations\n",
+            "\n",
+            "#### How to use\n",
+            "\n",
+            "```python\n",
+            "# TODO: add an example code snippet for running this diffusion pipeline\n",
+            "```\n",
+            "\n",
+            "#### Limitations and bias\n",
+            "\n",
+            "[TODO: provide examples of latent issues and potential remediations]\n",
+            "\n",
+            "## Training details\n",
+            "\n",
+            "[TODO: describe the data used to train the model]"
+          ]
+        }
+      ]
+    }
+  ]
+}

README.md

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+---
+license: creativeml-openrail-m
+library_name: diffusers
+tags:
+- stable-diffusion-xl
+- stable-diffusion-xl-diffusers
+- text-to-image
+- diffusers
+- textual_inversion
+inference: true
+base_model: runwayml/stable-diffusion-v1-5
+---
+
+<!-- This model card has been generated automatically according to the information the training script had access to. You
+should probably proofread and complete it, then remove this comment. -->
+
+
+    # Textual inversion text2image fine-tuning - Bhavay-2001/textual-inversion
+    These are textual inversion adaption weights for runwayml/stable-diffusion-v1-5. You can find some example images in the following. 
+
+    ![img_0](./image_0.png)
+![img_1](./image_1.png)
+![img_2](./image_2.png)
+
+    
+
+## Intended uses & limitations
+
+#### How to use
+
+```python
+# TODO: add an example code snippet for running this diffusion pipeline
+```
+
+#### Limitations and bias
+
+[TODO: provide examples of latent issues and potential remediations]
+
+## Training details
+
+[TODO: describe the data used to train the model]