Created using Colab

Author: ruchira-net

stable_diffusion.ipynb

@@ -0,0 +1,107 @@
+{
+  "nbformat": 4,
+  "nbformat_minor": 0,
+  "metadata": {
+    "colab": {
+      "name": "stable-diffusion.ipynb",
+      "private_outputs": true,
+      "provenance": [],
+      "include_colab_link": true
+    },
+    "kernelspec": {
+      "name": "python3",
+      "display_name": "Python 3"
+    },
+    "language_info": {
+      "name": "python"
+    },
+    "accelerator": "GPU",
+    "gpuClass": "standard"
+  },
+  "cells": [
+    {
+      "cell_type": "markdown",
+      "metadata": {
+        "id": "view-in-github",
+        "colab_type": "text"
+      },
+      "source": [
+        "<a href=\"https://colab.research.google.com/github/ruchira-net/css-loader/blob/master/stable_diffusion.ipynb\" target=\"_parent\"><img src=\"https://colab.research.google.com/assets/colab-badge.svg\" alt=\"Open In Colab\"/></a>"
+      ]
+    },
+    {
+      "cell_type": "code",
+      "source": [
+        "%pip install --quiet --upgrade diffusers transformers accelerate mediapy peft"
+      ],
+      "metadata": {
+        "id": "ufD_d64nr08H"
+      },
+      "execution_count": null,
+      "outputs": []
+    },
+    {
+      "cell_type": "code",
+      "source": [
+        "import mediapy as media\n",
+        "import random\n",
+        "import sys\n",
+        "import torch\n",
+        "\n",
+        "from diffusers import DiffusionPipeline, TCDScheduler\n",
+        "from huggingface_hub import hf_hub_download\n",
+        "\n",
+        "# Choose either 8 or 12 steps:\n",
+        "num_inference_steps = 35\n",
+        "\n",
+        "base_model_id = \"stabilityai/stable-diffusion-xl-base-1.0\"\n",
+        "repo_name = \"ByteDance/Hyper-SD\"\n",
+        "plural = \"s\" if num_inference_steps > 1 else \"\"\n",
+        "ckpt_name = f\"Hyper-SDXL-{num_inference_steps}step{plural}-CFG-lora.safetensors\"\n",
+        "device = \"cuda\"\n",
+        "\n",
+        "pipe = DiffusionPipeline.from_pretrained(base_model_id, torch_dtype=torch.float16, variant=\"fp16\").to(device)\n",
+        "pipe.load_lora_weights(hf_hub_download(repo_name, ckpt_name))\n",
+        "pipe.fuse_lora()\n",
+        "pipe.scheduler = TCDScheduler.from_config(pipe.scheduler.config)"
+      ],
+      "metadata": {
+        "id": "bG2hkmSEvByV"
+      },
+      "execution_count": null,
+      "outputs": []
+    },
+    {
+      "cell_type": "code",
+      "source": [
+        "prompt = \"a photo of Pikachu fine dining with a view to the Eiffel Tower\"\n",
+        "negative_prompt = \"text\"\n",
+        "seed = random.randint(0, sys.maxsize)\n",
+        "\n",
+        "# Pick a value between 5.0 and 8.0:\n",
+        "guidance_scale = 7\n",
+        "\n",
+        "# Decrease eta (min: 0, max: 1.0) to get more details with multi-step inference:\n",
+        "eta = 0.5\n",
+        "\n",
+        "images = pipe(\n",
+        "    prompt = prompt,\n",
+        "    negative_prompt = negative_prompt,\n",
+        "    num_inference_steps = num_inference_steps,\n",
+        "    guidance_scale = guidance_scale,\n",
+        "    eta = eta,\n",
+        "    generator = torch.Generator(device).manual_seed(seed),\n",
+        "    ).images\n",
+        "\n",
+        "print(f\"Prompt:\\t{prompt}\\nSeed:\\t{seed}\")\n",
+        "media.show_images(images)\n",
+        "images[0].save(\"output.jpg\")"
+      ],
+      "metadata": {
+        "id": "AUc4QJfE-uR9"
+      },
+      "execution_count": null,
+      "outputs": []
+    }
+  ]
+}