Upload sd_to_diff_hub.ipynb with huggingface_hub

sd_to_diff_hub.ipynb

@@ -0,0 +1,268 @@
+{
+ "cells": [
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "24817911-0228-4434-bd3f-9ca50e9d8763",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "pwd"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "9c703396-7a83-4bb8-8faf-6f51550c0b4e",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "!(python scripts/convert_sd_to_diffusers.py \\\n",
+    "    --checkpoint_path logs/2023-10-22T14-53-45_pokemon/checkpoints/epoch=000202.ckpt \\\n",
+    "    --original_config_file configs/stable-diffusion/pokemon.yaml \\\n",
+    "    --dump_path tf_202 \\\n",
+    "    --use_ema \\\n",
+    ")"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "0f86f81a-21ce-4bac-8e9d-517bd0200b9c",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "from huggingface_hub import notebook_login\n",
+    "\n",
+    "notebook_login()"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "1b2be122-0c7d-4c99-84f0-70955d356721",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "# @title Upload a locally saved pipeline to the hub\n",
+    "\n",
+    "# Code to upload a pipeline saved locally to the hub\n",
+    "from huggingface_hub import HfApi, ModelCard, create_repo, get_full_repo_name\n",
+    "\n",
+    "# Set up repo and upload files\n",
+    "model_name = \"tradfusion-v2\"  # @param What you want it called on the hub\n",
+    "local_folder_name = \"tf_202\"  # @param Created by the script or one you created via image_pipe.save_pretrained('save_name')\n",
+    "description = \"Fine-tuned Stable Diffusion Model on Irish Traditional Tunes Spectrograms\"  # @param\n",
+    "checkpoint_path = \"logs/2023-10-22T14-53-45_pokemon/checkpoints\"\n",
+    "hub_model_id = get_full_repo_name(model_name)\n",
+    "create_repo(hub_model_id)\n",
+    "api = HfApi()\n",
+    "api.upload_folder(\n",
+    "    folder_path=f\"{local_folder_name}/feature_extractor\", path_in_repo=\"feature_extractor\", repo_id=hub_model_id\n",
+    ")\n",
+    "api.upload_folder(\n",
+    "    folder_path=f\"{local_folder_name}/safety_checker\", path_in_repo=\"safety_checker\", repo_id=hub_model_id\n",
+    ")\n",
+    "api.upload_folder(\n",
+    "    folder_path=f\"{local_folder_name}/scheduler\", path_in_repo=\"scheduler\", repo_id=hub_model_id\n",
+    ")\n",
+    "api.upload_folder(\n",
+    "    folder_path=f\"{local_folder_name}/text_encoder\", path_in_repo=\"text_encoder\", repo_id=hub_model_id\n",
+    ")\n",
+    "api.upload_folder(\n",
+    "    folder_path=f\"{local_folder_name}/tokenizer\", path_in_repo=\"tokenizer\", repo_id=hub_model_id\n",
+    ")\n",
+    "api.upload_folder(\n",
+    "    folder_path=f\"{local_folder_name}/unet\", path_in_repo=\"unet\", repo_id=hub_model_id\n",
+    ")\n",
+    "api.upload_folder(\n",
+    "    folder_path=f\"{local_folder_name}/vae\", path_in_repo=\"vae\", repo_id=hub_model_id\n",
+    ")\n",
+    "api.upload_file(\n",
+    "    path_or_fileobj=f\"{local_folder_name}/model_index.json\",\n",
+    "    path_in_repo=\"model_index.json\",\n",
+    "    repo_id=hub_model_id,\n",
+    ")\n",
+    "api.upload_file(\n",
+    "    path_or_fileobj=f\"{checkpoint_path}/epoch=000202.ckpt\",\n",
+    "    path_in_repo=\"checkpoint_epoch202.ckpt\",\n",
+    "    repo_id=hub_model_id,\n",
+    ")\n",
+    "# Add a model card (optional but nice!)\n",
+    "content = f\"\"\"\n",
+    "---\n",
+    "license: mit\n",
+    "tags:\n",
+    "- pytorch\n",
+    "- diffusers\n",
+    "- unconditional-image-generation\n",
+    "- text-to-image\n",
+    "- diffusion-models-class\n",
+    "---\n",
+    "\n",
+    "# Example Fine-Tuned Model for Unit 2 of the [Diffusion Models Class 🧨](https://github.com/huggingface/diffusion-models-class)\n",
+    "\n",
+    "{description}\n",
+    "\n",
+    "## Usage\n",
+    "\n",
+    "```python\n",
+    "from diffusers import StableDiffusionPipeline\n",
+    "\n",
+    "pipeline = StableDiffusionPipeline.from_pretrained('{hub_model_id}')\n",
+    "image = pipeline().images[0]\n",
+    "image\n",
+    "```\n",
+    "\"\"\"\n",
+    "\n",
+    "card = ModelCard(content)\n",
+    "card.push_to_hub(hub_model_id)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "d4efff90-7300-4017-b0af-3ffafdb1eb9e",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "# @title Upload a locally saved pipeline to the hub\n",
+    "\n",
+    "# Code to upload a pipeline saved locally to the hub\n",
+    "from huggingface_hub import HfApi, ModelCard, create_repo, get_full_repo_name\n",
+    "\n",
+    "# Set up repo and upload files\n",
+    "model_name = \"tradfusion-v2-training-files\"  # @param What you want it called on the hub\n",
+    "local_folder_name = \"logs/2023-10-22T14-53-45_pokemon\"  # @param Created by the script or one you created via image_pipe.save_pretrained('save_name')\n",
+    "#description = \"Fine-tuned Stable Diffusion Model on Irish Traditional Tunes Spectrograms\"  # @param\n",
+    "checkpoint_path = \"logs/2023-10-22T14-53-45_pokemon/checkpoints\"\n",
+    "hub_model_id = get_full_repo_name(model_name)\n",
+    "#create_repo(hub_model_id)\n",
+    "api = HfApi()\n",
+    "api.upload_folder(\n",
+    "    folder_path=f\"{local_folder_name}/configs\", path_in_repo=\"configs\", repo_id=hub_model_id\n",
+    ")\n",
+    "api.upload_folder(\n",
+    "    folder_path=f\"{local_folder_name}/images\", path_in_repo=\"images\", repo_id=hub_model_id\n",
+    ")\n",
+    "api.upload_folder(\n",
+    "    folder_path=f\"{local_folder_name}/testtube/version_0/tf\", path_in_repo=\"tf\", repo_id=hub_model_id\n",
+    ")\n",
+    "api.upload_file(\n",
+    "    path_or_fileobj=f\"{local_folder_name}/testtube/version_0/metrics.csv\",\n",
+    "    path_in_repo=\"metrics.csv\",\n",
+    "    repo_id=hub_model_id,\n",
+    ")\n",
+    "api.upload_file(\n",
+    "    path_or_fileobj=f\"{checkpoint_path}/epoch=000169.ckpt\",\n",
+    "    path_in_repo=\"checkpoint_epoch169.ckpt\",\n",
+    "    repo_id=hub_model_id,\n",
+    ")\n",
+    "api.upload_file(\n",
+    "    path_or_fileobj=f\"{checkpoint_path}/epoch=000183.ckpt\",\n",
+    "    path_in_repo=\"checkpoint_epoch183.ckpt\",\n",
+    "    repo_id=hub_model_id,\n",
+    ")\n",
+    "api.upload_file(\n",
+    "    path_or_fileobj=f\"{checkpoint_path}/epoch=000189.ckpt\",\n",
+    "    path_in_repo=\"checkpoint_epoch189.ckpt\",\n",
+    "    repo_id=hub_model_id,\n",
+    ")\n",
+    "api.upload_file(\n",
+    "    path_or_fileobj=f\"{checkpoint_path}/epoch=000193.ckpt\",\n",
+    "    path_in_repo=\"checkpoint_epoch193.ckpt\",\n",
+    "    repo_id=hub_model_id,\n",
+    ")\n",
+    "api.upload_file(\n",
+    "    path_or_fileobj=f\"{checkpoint_path}/epoch=000196.ckpt\",\n",
+    "    path_in_repo=\"checkpoint_epoch196.ckpt\",\n",
+    "    repo_id=hub_model_id,\n",
+    ")\n",
+    "api.upload_file(\n",
+    "    path_or_fileobj=f\"{checkpoint_path}/epoch=000199.ckpt\",\n",
+    "    path_in_repo=\"checkpoint_epoch199.ckpt\",\n",
+    "    repo_id=hub_model_id,\n",
+    ")\n",
+    "api.upload_file(\n",
+    "    path_or_fileobj=f\"{checkpoint_path}/epoch=000202.ckpt\",\n",
+    "    path_in_repo=\"checkpoint_epoch202.ckpt\",\n",
+    "    repo_id=hub_model_id,\n",
+    ")\n",
+    "api.upload_file(\n",
+    "    path_or_fileobj=f\"{checkpoint_path}/last.ckpt\",\n",
+    "    path_in_repo=\"checkpoint_last.ckpt\",\n",
+    "    repo_id=hub_model_id,\n",
+    ")\n",
+    "# Add a model card (optional but nice!)\n",
+    "content = f\"\"\"\n",
+    "---\n",
+    "license: mit\n",
+    "tags:\n",
+    "- pytorch\n",
+    "- diffusers\n",
+    "- text-to-image\n",
+    "---\n",
+    "\n",
+    "## Usage\n",
+    "\n",
+    "Files logged during training, tensorboard, images generated, metrics and varias checkpoints\n",
+    "\"\"\"\n",
+    "\n",
+    "#card = ModelCard(content)\n",
+    "#card.push_to_hub(hub_model_id)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "66cafa2d-ba4b-4086-8694-fb52911e453c",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "# @title Upload a locally saved pipeline to the hub\n",
+    "\n",
+    "# Code to upload a pipeline saved locally to the hub\n",
+    "from huggingface_hub import HfApi, ModelCard, create_repo, get_full_repo_name\n",
+    "\n",
+    "# Set up repo and upload files\n",
+    "model_name = \"tradfusion-v2-training-files\"  # @param What you want it called on the hub\n",
+    "local_folder_name = \"wo\"  # @param Created by the script or one you created via image_pipe.save_pretrained('save_name')\n",
+    "checkpoint_path = \"logs/2023-10-22T14-53-45_pokemon/checkpoints\"\n",
+    "hub_model_id = get_full_repo_name(model_name)\n",
+    "\n",
+    "api = HfApi()\n",
+    "api.upload_file(\n",
+    "    path_or_fileobj=f\"{checkpoint_path}/epoch=000202.ckpt\",\n",
+    "    path_in_repo=\"checkpoint_epoch202.ckpt\",\n",
+    "    repo_id=hub_model_id,\n",
+    ")\n",
+    "api.upload_file(\n",
+    "    path_or_fileobj=f\"{checkpoint_path}/last.ckpt\",\n",
+    "    path_in_repo=\"checkpoint_last.ckpt\",\n",
+    "    repo_id=hub_model_id,\n",
+    ")\n"
+   ]
+  }
+ ],
+ "metadata": {
+  "kernelspec": {
+   "display_name": "Python 3 (ipykernel)",
+   "language": "python",
+   "name": "python3"
+  },
+  "language_info": {
+   "codemirror_mode": {
+    "name": "ipython",
+    "version": 3
+   },
+   "file_extension": ".py",
+   "mimetype": "text/x-python",
+   "name": "python",
+   "nbconvert_exporter": "python",
+   "pygments_lexer": "ipython3",
+   "version": "3.10.6"
+  }
+ },
+ "nbformat": 4,
+ "nbformat_minor": 5
+}