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{
"nbformat": 4,
"nbformat_minor": 0,
"metadata": {
"colab": {
"provenance": []
},
"kernelspec": {
"name": "python3",
"display_name": "Python 3"
},
"language_info": {
"name": "python"
}
},
"cells": [
{
"cell_type": "markdown",
"source": [
"Run both of the following two codes"
],
"metadata": {
"id": "OnuCk_wNLM_D"
}
},
{
"cell_type": "code",
"source": [
"from google.colab import drive \n",
"drive.mount(\"/content/drive\")"
],
"metadata": {
"id": "liEiK8Iioscq"
},
"execution_count": null,
"outputs": []
},
{
"cell_type": "code",
"source": [
"!pip install torch safetensors\n",
"!pip install wget"
],
"metadata": {
"id": "pXr7oNJzwwgU"
},
"execution_count": null,
"outputs": []
},
{
"cell_type": "markdown",
"source": [
"Replace the following links, etc. with the desired ones and then run the following code"
],
"metadata": {
"id": "7Ils-K70k15Y"
}
},
{
"cell_type": "code",
"source": [
"#@title <font size=\"-0\">Download Models</font>\n",
"#@markdown Please specify the model name or download link for Google Drive, separated by commas\n",
"#@markdown - If it is the model name on Google Drive, specify it as a relative path to My Drive\n",
"#@markdown - If it is a download link, copy the link address by right-clicking and paste it in place of the link below\n",
"\n",
"import shutil\n",
"import urllib.parse\n",
"import urllib.request\n",
"import wget\n",
"\n",
"models = \"Please use your own model in place of this example, example.safetensors, https://huggingface.co./stabilityai/stable-diffusion-2-1/resolve/main/v2-1_768-ema-pruned.ckpt\" #@param {type:\"string\"}\n",
"models = [m.strip() for m in models.split(\",\") if not models == \"\"]\n",
"for model in models:\n",
" if 0 < len(urllib.parse.urlparse(model).scheme): # if model is url\n",
" wget.download(model)\n",
" # once the bug on python 3.8 is fixed, replace the above code with the following code\n",
" ## model_data = urllib.request.urlopen(model).read()\n",
" ## with open(os.path.basename(model), mode=\"wb\") as f:\n",
" ## f.write(model_data)\n",
" elif model.endswith((\".ckpt\", \".safetensors\", \".pt\", \".pth\")):\n",
" from_ = \"/content/drive/MyDrive/\" + model\n",
" to_ = \"/content/\" + model\n",
" shutil.copy(from_, to_)\n",
" else:\n",
" print(f\"\\\"{model}\\\"はURLではなく、正しい形式のファイルでもありません\")"
],
"metadata": {
"cellView": "form",
"id": "4vd3A09AxJE0"
},
"execution_count": null,
"outputs": []
},
{
"cell_type": "markdown",
"source": [
"if you use a relatively newer model such as SD2.1, run the following code"
],
"metadata": {
"id": "m1mHzOMjcDhz"
}
},
{
"cell_type": "code",
"source": [
"!pip install pytorch-lightning"
],
"metadata": {
"id": "TkrmByc0aYVN"
},
"execution_count": null,
"outputs": []
},
{
"cell_type": "markdown",
"source": [
"Run either of the following two codes. If you run out of memory and crash, use a smaller model or a paid high-memory runtime"
],
"metadata": {
"id": "0SUK6Alv2ItS"
}
},
{
"cell_type": "code",
"source": [
"#@title <font size=\"-0\">If you specify the name of the model you want to convert and convert it manually</font>\n",
"import os\n",
"import torch\n",
"import safetensors.torch\n",
"\n",
"model = \"v2-1_768-ema-pruned.ckpt\" #@param {type:\"string\"}\n",
"model_name, model_ext = os.path.splitext(model)\n",
"as_fp16 = True #@param {type:\"boolean\"}\n",
"save_directly_to_Google_Drive = True #@param {type:\"boolean\"}\n",
"\n",
"with torch.no_grad():\n",
" if model_ext == \".safetensors\":\n",
" weights = safetensors.torch.load_file(model_name + model_ext, device=\"cpu\")\n",
" elif model_ext == \".ckpt\":\n",
" weights = torch.load(model_name + model_ext, map_location=torch.device('cpu'))[\"state_dict\"]\n",
" else:\n",
" raise Exception(\"対応形式は.ckptと.safetensorsです\\n\" + f\"\\\"{model}\\\"は対応形式ではありません\")\n",
" if as_fp16:\n",
" model_name = model_name + \"-fp16\"\n",
" for key in weights.keys():\n",
" weights[key] = weights[key].half()\n",
" if save_directly_to_Google_Drive:\n",
" os.chdir(\"/content/drive/MyDrive\")\n",
" safetensors.torch.save_file(weights, model_name + \".safetensors\")\n",
" os.chdir(\"/content\")\n",
" else:\n",
" safetensors.torch.save_file(weights, model_name + \".safetensors\")\n",
" del weights\n",
"\n",
"!reset"
],
"metadata": {
"id": "9OmSG98HxJg2",
"cellView": "form"
},
"execution_count": null,
"outputs": []
},
{
"cell_type": "code",
"source": [
"#@title <font size=\"-0\">If you automatically convert all pre-loaded models</font>\n",
"import os\n",
"import glob\n",
"import torch\n",
"import safetensors.torch\n",
"\n",
"as_fp16 = True #@param {type:\"boolean\"}\n",
"save_directly_to_Google_Drive = True #@param {type:\"boolean\"}\n",
"\n",
"with torch.no_grad():\n",
" model_paths = glob.glob(r\"/content/*.ckpt\") + glob.glob(r\"/content/*.safetensors\") + glob.glob(r\"/content/*.pt\") + glob.glob(r\"/content/*.pth\")\n",
" for model_path in model_paths:\n",
" model_name, model_ext = os.path.splitext(os.path.basename(model_path))\n",
" if model_ext == \".safetensors\":\n",
" weights = safetensors.torch.load_file(model_name + model_ext, device=\"cpu\")\n",
" elif model_ext == \".ckpt\":\n",
" weights = torch.load(model_name + model_ext, map_location=torch.device('cpu'))[\"state_dict\"]\n",
" else:\n",
" print(\"対応形式は.ckpt\tと.safetensorsです\\n\" + f\"\\\"{model}\\\"は対応形式ではありません\")\n",
" break\n",
" if as_fp16:\n",
" model_name = model_name + \"-fp16\"\n",
" for key in weights.keys():\n",
" weights[key] = weights[key].half()\n",
" if save_directly_to_Google_Drive:\n",
" os.chdir(\"/content/drive/MyDrive\")\n",
" safetensors.torch.save_file(weights, model_name + \".safetensors\")\n",
" os.chdir(\"/content\")\n",
" else:\n",
" safetensors.torch.save_file(weights, model_name + \".safetensors\")\n",
" del weights\n",
"\n",
"!reset"
],
"metadata": {
"id": "5TUvrW5VzLst",
"cellView": "form"
},
"execution_count": null,
"outputs": []
},
{
"cell_type": "markdown",
"source": [
"Choose your favorite model from https://huggingface.co./models?other=stable-diffusion or other model link collections"
],
"metadata": {
"id": "yaLq5Nqe6an6"
}
}
]
} |