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README.md +45 -0
image_0.png +0 -0
image_2.png +0 -0
test_model_card_controlnet_sdxl.ipynb +620 -0

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+---
+license: openrail++
+library_name: diffusers
+tags:
+- stable-diffusion-xl
+- stable-diffusion-xl-diffusers
+- text-to-image
+- diffusers
+- controlnet
+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. -->
+# controlnet-camaro/test
+These are controlnet weights trained on runwayml/stable-diffusion-v1-5 with new type of conditioning.
+You can find some example images below.
+prompt: validation_prompt
+![images_0)](./images_0.png)
+prompt: validation_prompt
+![images_1)](./images_1.png)
+prompt: validation_prompt
+![images_2)](./images_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]

image_0.png ADDED Viewed

image_2.png ADDED Viewed

test_model_card_controlnet_sdxl.ipynb ADDED Viewed

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+{
+  "cells": [
+    {
+      "cell_type": "code",
+      "source": [
+        "!git clone https://github.com/bamps53/diffusers\n",
+        "%cd diffusers\n",
+        "!git checkout 0f443c8b897c0bb9c034e524d1ab1127ab88d587\n",
+        "!pip install -q -e \".[dev]\""
+      ],
+      "metadata": {
+        "colab": {
+          "base_uri": "https://localhost:8080/"
+        },
+        "id": "ZNgWSJQ-BViA",
+        "outputId": "f57c7bf5-2b70-4861-858a-bf3dec0f3690"
+      },
+      "id": "ZNgWSJQ-BViA",
+      "execution_count": 1,
+      "outputs": [
+        {
+          "output_type": "stream",
+          "name": "stdout",
+          "text": [
+            "/content/diffusers\n"
+          ]
+        }
+      ]
+    },
+    {
+      "cell_type": "code",
+      "source": [
+        "!wget https://huggingface.co/sayakpaul/test-model-card-template-dreambooth/resolve/main/image_0.png\n",
+        "!wget https://huggingface.co/sayakpaul/test-model-card-template-dreambooth/resolve/main/image_1.png\n",
+        "!wget https://huggingface.co/sayakpaul/test-model-card-template-dreambooth/resolve/main/image_2.png"
+      ],
+      "metadata": {
+        "colab": {
+          "base_uri": "https://localhost:8080/"
+        },
+        "id": "pdpDJAul40ZB",
+        "outputId": "0f86603d-cef1-4a23-b2b6-afc3a4390522"
+      },
+      "id": "pdpDJAul40ZB",
+      "execution_count": 2,
+      "outputs": [
+        {
+          "output_type": "stream",
+          "name": "stdout",
+          "text": [
+            "--2024-02-08 13:47:00--  https://huggingface.co/sayakpaul/test-model-card-template-dreambooth/resolve/main/image_0.png\n",
+            "Resolving huggingface.co (huggingface.co)... 3.163.189.114, 3.163.189.37, 3.163.189.90, ...\n",
+            "Connecting to huggingface.co (huggingface.co)|3.163.189.114|:443... connected.\n",
+            "HTTP request sent, awaiting response... 200 OK\n",
+            "Length: 386612 (378K) [image/png]\n",
+            "Saving to: ‘image_0.png’\n",
+            "\n",
+            "image_0.png         100%[===================>] 377.55K  --.-KB/s    in 0.1s    \n",
+            "\n",
+            "2024-02-08 13:47:00 (2.84 MB/s) - ‘image_0.png’ saved [386612/386612]\n",
+            "\n",
+            "--2024-02-08 13:47:00--  https://huggingface.co/sayakpaul/test-model-card-template-dreambooth/resolve/main/image_1.png\n",
+            "Resolving huggingface.co (huggingface.co)... 3.163.189.114, 3.163.189.37, 3.163.189.90, ...\n",
+            "Connecting to huggingface.co (huggingface.co)|3.163.189.114|:443... connected.\n",
+            "HTTP request sent, awaiting response... 200 OK\n",
+            "Length: 386612 (378K) [image/png]\n",
+            "Saving to: ‘image_1.png’\n",
+            "\n",
+            "image_1.png         100%[===================>] 377.55K  --.-KB/s    in 0.03s   \n",
+            "\n",
+            "2024-02-08 13:47:00 (14.1 MB/s) - ‘image_1.png’ saved [386612/386612]\n",
+            "\n",
+            "--2024-02-08 13:47:00--  https://huggingface.co/sayakpaul/test-model-card-template-dreambooth/resolve/main/image_2.png\n",
+            "Resolving huggingface.co (huggingface.co)... 3.163.189.114, 3.163.189.37, 3.163.189.90, ...\n",
+            "Connecting to huggingface.co (huggingface.co)|3.163.189.114|:443... connected.\n",
+            "HTTP request sent, awaiting response... 200 OK\n",
+            "Length: 386612 (378K) [image/png]\n",
+            "Saving to: ‘image_2.png’\n",
+            "\n",
+            "image_2.png         100%[===================>] 377.55K  --.-KB/s    in 0.07s   \n",
+            "\n",
+            "2024-02-08 13:47:01 (5.29 MB/s) - ‘image_2.png’ saved [386612/386612]\n",
+            "\n"
+          ]
+        }
+      ]
+    },
+    {
+      "cell_type": "code",
+      "source": [
+        "from diffusers.utils import load_image\n",
+        "from examples.controlnet.train_controlnet_sdxl import save_model_card\n",
+        "\n",
+        "images = [load_image(f\"image_{i}.png\") for i in range(3)]\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",
+        "save_model_card(\n",
+        "    repo_id=\"camaro/test\",\n",
+        "    image_logs=image_logs,\n",
+        "    base_model=\"runwayml/stable-diffusion-v1-5\",\n",
+        "    repo_folder=\".\",\n",
+        ")"
+      ],
+      "metadata": {
+        "colab": {
+          "base_uri": "https://localhost:8080/",
+          "height": 190,
+          "referenced_widgets": [
+            "6af63801222041e084b8dcc7d9717ea0",
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+            "78e8a8b996cc44138e8afcf00264be7c",
+            "442696138b0f431e93e0fa7ac7bd5f6d",
+            "aec159b072b64f1a8f5d28c09f2a0724",
+            "57b051e7336947c5bab73128a0b50996",
+            "39688812a2ff48bf9a77025ad5e0c55b",
+            "8fcc3694f4e44f528b257dffe7e46f30",
+            "3491736d5fa044db9da7df84d0bcf4d3",
+            "b7060bfb30304f22a16f0a557e32bbe3"
+          ]
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+        "id": "v7vs7eQyDeX1",
+        "outputId": "2dc7fcf4-b6ec-4ee4-b951-872f28e510d0"
+      },
+      "id": "v7vs7eQyDeX1",
+      "execution_count": 2,
+      "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]"
+            ],
+            "application/vnd.jupyter.widget-view+json": {
+              "version_major": 2,
+              "version_minor": 0,
+              "model_id": "6af63801222041e084b8dcc7d9717ea0"
+            }
+          },
+          "metadata": {}
+        },
+        {
+          "output_type": "stream",
+          "name": "stderr",
+          "text": [
+            "/usr/local/lib/python3.10/dist-packages/huggingface_hub/utils/_token.py:88: 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"
+          ]
+        }
+      ]
+    },
+    {
+      "cell_type": "code",
+      "execution_count": 3,
+      "id": "b19ff19c-fff0-469f-b004-dd731edbffa9",
+      "metadata": {
+        "colab": {
+          "base_uri": "https://localhost:8080/"
+        },
+        "id": "b19ff19c-fff0-469f-b004-dd731edbffa9",
+        "outputId": "f1248d0f-9909-44b5-d0e8-72ceab6640a2"
+      },
+      "outputs": [
+        {
+          "output_type": "stream",
+          "name": "stdout",
+          "text": [
+            "---\n",
+            "license: openrail++\n",
+            "library_name: diffusers\n",
+            "tags:\n",
+            "- stable-diffusion-xl\n",
+            "- stable-diffusion-xl-diffusers\n",
+            "- text-to-image\n",
+            "- diffusers\n",
+            "- controlnet\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",
+            "# controlnet-camaro/test\n",
+            "\n",
+            "These are controlnet weights trained on runwayml/stable-diffusion-v1-5 with new type of conditioning.\n",
+            "You can find some example images below.\n",
+            "prompt: validation_prompt\n",
+            "![images_0)](./images_0.png)\n",
+            "prompt: validation_prompt\n",
+            "![images_1)](./images_1.png)\n",
+            "prompt: validation_prompt\n",
+            "![images_2)](./images_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]"
+          ]
+        }
+      ],
+      "source": [
+        "!cat README.md"
+      ]
+    },
+    {
+      "cell_type": "code",
+      "source": [],
+      "metadata": {
+        "id": "Y3uTj1bv5Amw"
+      },
+      "id": "Y3uTj1bv5Amw",
+      "execution_count": null,
+      "outputs": []
+    }
+  ],
+  "metadata": {
+    "kernelspec": {
+      "display_name": "Python 3",
+      "name": "python3"
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+    "language_info": {
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+        "version": 3
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+      "pygments_lexer": "ipython3",
+      "version": "3.9.17"
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