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{
"cells": [
{
"cell_type": "markdown",
"metadata": {
"id": "grG2f8fRZI6V",
"tags": []
},
"source": [
"# **StableDiffusion SageMaker version by @marat_ai**\n",
"\n",
"\n",
" **[YouTube](https://www.youtube.com/watch?v=dQw4w9WgXcQ)** |  **[sdg.marat@gmail.com]** |\n",
"\n",
"\n",
"_That notebook creates a local instance that constantly saves to your Amazon storage, so you don't need to download all models and install all requirements every time. Only once._"
]
},
{
"cell_type": "markdown",
"metadata": {
"id": "RE1n8kLOZI6Y",
"jp-MarkdownHeadingCollapsed": true,
"tags": []
},
"source": [
"# **STEP 1** (Runs only once!)\n",
"## Requirements 👇\n",
"* _Don't forget to specify your ngroc token_"
]
},
{
"cell_type": "code",
"execution_count": 1,
"metadata": {
"id": "A1p2bOziZI6Y",
"tags": []
},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"\u001b[1;32mDone!\n"
]
}
],
"source": [
"print('\u001b[1;32mInstalling requirements...')\n",
"\n",
"from IPython.display import clear_output\n",
"!conda install -c conda-forge libglib -y & conda update -n base conda -y\n",
"\n",
"!pip install tqdm\n",
"\n",
"clear_output()\n",
"print('\u001b[1;32mDone! Conda installed!')\n",
"\n",
"!git clone https://github.com/rocketpal/stable-diffusion-webui\n",
"%cd stable-diffusion-webui\n",
"\n",
"'''\n",
"%pip install -r requirements.txt --quiet\n",
"'''\n",
"\n",
"#ControlNet ext\n",
"\n",
"%cd /home/studio-lab-user/stable-diffusion-webui/extensions/\n",
"!git clone https://github.com/rocketpal/sd-webui-controlnet\n",
"%cd /home/studio-lab-user/stable-diffusion-webui\n",
"\n",
"clear_output()\n",
"print('\u001b[1;32mDone!')"
]
},
{
"cell_type": "markdown",
"metadata": {
"id": "7tJLpUoHZI6Z",
"jp-MarkdownHeadingCollapsed": true,
"tags": []
},
"source": [
"# **STEP 2.1** (Runs only once!)\n",
"## Download Base models 👇\n",
"\n",
"* Don't forget to run the cell bellow!"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {
"id": "FQyXmO0fZI6a",
"tags": []
},
"outputs": [],
"source": [
"#Base models:\n",
"\n",
"model_link1 = 'https://huggingface.co/SG161222/Realistic_Vision_V5.1_noVAE/resolve/main/Realistic_Vision_V5.1.safetensors'\n",
"model_link2 = ''\n",
"model_link3 = ''\n",
"model_link4 = ''\n",
"model_link5 = ''\n",
"\n",
"\n",
"\n",
"\n",
"\n",
"\n",
"\n",
"\n",
"\n",
"\n",
"\n",
"\n",
"\n",
"\n",
"#Run this to download base models:\n",
"\n",
"import os\n",
"import requests\n",
"from tqdm import tqdm\n",
"\n",
"# Function to download a file with progress\n",
"def download_file(url, target_dir):\n",
" filename = url.split(\"/\")[-1] # Extract the filename from the URL\n",
" download_path = os.path.join(target_dir, filename)\n",
" response = requests.get(url, stream=True)\n",
" total_size = int(response.headers.get(\"content-length\", 0))\n",
" block_size = 1024 # 1 Kibibyte\n",
"\n",
" with open(download_path, \"wb\") as file, tqdm(\n",
" desc=filename,\n",
" total=total_size,\n",
" unit=\"B\",\n",
" unit_scale=True,\n",
" unit_divisor=1024,\n",
" ) as bar:\n",
" for data in response.iter_content(block_size):\n",
" file.write(data)\n",
" bar.update(len(data))\n",
"\n",
"\n",
"\n",
"#Base models\n",
"download_links = [model_link1,\n",
" model_link2,\n",
" model_link3,\n",
" model_link4,\n",
" model_link5\n",
" ]\n",
"\n",
"\n",
"target_dir = \"/home/studio-lab-user/stable-diffusion-webui/models/Stable-diffusion/\"\n",
"\n",
"# Loop through the download links and download files to the target directory\n",
"for link in download_links:\n",
" if link == '':\n",
" pass\n",
" else:\n",
" download_file(link, target_dir)"
]
},
{
"cell_type": "markdown",
"metadata": {
"id": "3wZXNNiHZI6c",
"jp-MarkdownHeadingCollapsed": true,
"tags": []
},
"source": [
"# **STEP 3**\n",
"## Run StableDiffusion 👇\n",
"Don't forget to specify your ngroc token!"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {
"_kg_hide-input": false,
"_kg_hide-output": false,
"id": "8af-hu-3ZI6c",
"tags": []
},
"outputs": [],
"source": [
"%cd ~/stable-diffusion-webui\n",
"!python launch.py --listen --xformers --enable-insecure-extension-access --gradio-queue --ngrok 2W3231xwzhftRMwLpIS0jiDd2lTNqs_6JmzFy51yhDQ85Q7NxeCT"
]
},
{
"cell_type": "markdown",
"metadata": {
"id": "xMNePTxDZI6c",
"jp-MarkdownHeadingCollapsed": true,
"tags": []
},
"source": [
"# **Maintenance**"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {
"id": "U3fphZyuZI6c",
"tags": []
},
"outputs": [],
"source": [
"#clean remove all env, cache and file\n",
"\n",
"!rm -r /home/studio-lab-user/.cache\n",
"!rm -r /home/studio-lab-user/.conda\n",
"!conda remove -n \"env_name\" --all\n",
"!rm -rf /home/studio-lab-user/*"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {
"id": "YApy5h6TZI6d"
},
"outputs": [],
"source": [
"#Check the storage available\n",
"!df -h | grep -E 'Avail|home'"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {
"id": "vwRdajvuZI6d",
"tags": []
},
"outputs": [],
"source": [
"#List all folders and sizes\n",
"!du -h --max-depth=1 /home/studio-lab-user"
]
}
],
"metadata": {
"colab": {
"collapsed_sections": [
"RE1n8kLOZI6Y",
"7tJLpUoHZI6Z",
"3wZXNNiHZI6c",
"xMNePTxDZI6c"
],
"provenance": []
},
"kernelspec": {
"display_name": "default:Python",
"language": "python",
"name": "conda-env-default-py"
},
"language_info": {
"codemirror_mode": {
"name": "ipython",
"version": 3
},
"file_extension": ".py",
"mimetype": "text/x-python",
"name": "python",
"nbconvert_exporter": "python",
"pygments_lexer": "ipython3",
"version": "3.9.16"
}
},
"nbformat": 4,
"nbformat_minor": 4
}
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