Upload Base_SD_SageMaker notebook03 (1).ipynb

Base_SD_SageMaker notebook03 (1).ipynb

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+{
+ "cells": [
+  {
+   "cell_type": "markdown",
+   "metadata": {
+    "id": "grG2f8fRZI6V",
+    "tags": []
+   },
+   "source": [
+    "# **StableDiffusion SageMaker version by @marat_ai**\n",
+    "\n",
+    "\n",
+    "![youtube.png](data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAABAAAAAQCAMAAAAoLQ9TAAAAJ1BMVEVHcEz/AAD/AAD/AAD/AAD/AAD/AAD/AAD/AAD/////mJj/wcH/jY3aUCqcAAAACHRSTlMA8czbELSvDrGIfzkAAABCSURBVBiVY2AgA7CwMTMycgABIyMzGztQgIkDCTABBThQAEyAixtNgIeTkwu/AIYWZEMxrGVhZWaE8BiZWVnI8RoAJWEEDt2WmW4AAAAASUVORK5CYII=) **[YouTube](https://www.youtube.com/watch?v=dQw4w9WgXcQ)** | ![youtube.png](data:image/png;base64,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) **[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
+}