add stable
This commit is contained in:
Cornelius Specht
parent
3d088112d1
commit
566e68d2f5
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{
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"cells": [
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{
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"cell_type": "code",
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"execution_count": 1,
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"id": "1f417fcf-52d5-4e49-9e26-3834eba323cf",
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"metadata": {
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"tags": []
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},
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"outputs": [
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{
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"name": "stdout",
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"output_type": "stream",
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"text": [
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"Collecting transformers\n",
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" Downloading transformers-4.45.0-py3-none-any.whl.metadata (44 kB)\n",
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"\u001b[2K \u001b[90m━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[32m44.4/44.4 kB\u001b[0m \u001b[31m1.3 MB/s\u001b[0m eta \u001b[36m0:00:00\u001b[0m\n",
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"\u001b[?25hCollecting diffusers\n",
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" Downloading diffusers-0.30.3-py3-none-any.whl.metadata (18 kB)\n",
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"Collecting accelerate\n",
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" Downloading accelerate-0.34.2-py3-none-any.whl.metadata (19 kB)\n",
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"Collecting huggingface-hub<1.0,>=0.23.2 (from transformers)\n",
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" Downloading huggingface_hub-0.25.1-py3-none-any.whl.metadata (13 kB)\n",
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"Collecting regex!=2019.12.17 (from transformers)\n",
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" Downloading regex-2024.9.11-cp311-cp311-manylinux_2_17_x86_64.manylinux2014_x86_64.whl.metadata (40 kB)\n",
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"\u001b[2K \u001b[90m━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[32m40.5/40.5 kB\u001b[0m \u001b[31m3.2 MB/s\u001b[0m eta \u001b[36m0:00:00\u001b[0m\n",
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"\u001b[?25hRequirement already satisfied: requests in /opt/conda/lib/python3.11/site-packages (from transformers) (2.31.0)\n",
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"Collecting tokenizers<0.21,>=0.20 (from transformers)\n",
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" Downloading tokenizers-0.20.0-cp311-cp311-manylinux_2_17_x86_64.manylinux2014_x86_64.whl.metadata (6.7 kB)\n",
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"Collecting safetensors>=0.4.1 (from transformers)\n",
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" Downloading safetensors-0.4.5-cp311-cp311-manylinux_2_17_x86_64.manylinux2014_x86_64.whl.metadata (3.8 kB)\n",
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"Requirement already satisfied: tqdm>=4.27 in /opt/conda/lib/python3.11/site-packages (from transformers) (4.66.1)\n",
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"Requirement already satisfied: torch>=1.10.0 in /opt/conda/lib/python3.11/site-packages (from accelerate) (2.3.0+cu118)\n",
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"Requirement already satisfied: comm>=0.1.3 in /opt/conda/lib/python3.11/site-packages (from ipywidgets) (0.2.1)\n",
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"Requirement already satisfied: ipython>=6.1.0 in /opt/conda/lib/python3.11/site-packages (from ipywidgets) (8.21.0)\n",
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"Requirement already satisfied: widgetsnbextension~=4.0.9 in /opt/conda/lib/python3.11/site-packages (from ipywidgets) (4.0.9)\n",
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"Requirement already satisfied: jupyterlab-widgets~=3.0.9 in /opt/conda/lib/python3.11/site-packages (from ipywidgets) (3.0.9)\n",
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"Requirement already satisfied: fsspec>=2023.5.0 in /opt/conda/lib/python3.11/site-packages (from huggingface-hub<1.0,>=0.23.2->transformers) (2023.12.2)\n",
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"Requirement already satisfied: typing-extensions>=3.7.4.3 in /opt/conda/lib/python3.11/site-packages (from huggingface-hub<1.0,>=0.23.2->transformers) (4.9.0)\n",
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"Requirement already satisfied: decorator in /opt/conda/lib/python3.11/site-packages (from ipython>=6.1.0->ipywidgets) (5.1.1)\n",
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"Requirement already satisfied: jedi>=0.16 in /opt/conda/lib/python3.11/site-packages (from ipython>=6.1.0->ipywidgets) (0.19.1)\n",
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"Requirement already satisfied: prompt-toolkit<3.1.0,>=3.0.41 in /opt/conda/lib/python3.11/site-packages (from ipython>=6.1.0->ipywidgets) (3.0.42)\n",
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"Requirement already satisfied: pygments>=2.4.0 in /opt/conda/lib/python3.11/site-packages (from ipython>=6.1.0->ipywidgets) (2.17.2)\n",
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"Requirement already satisfied: jinja2 in /opt/conda/lib/python3.11/site-packages (from torch>=1.10.0->accelerate) (3.1.3)\n",
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"Requirement already satisfied: nvidia-cuda-nvrtc-cu11==11.8.89 in /opt/conda/lib/python3.11/site-packages (from torch>=1.10.0->accelerate) (11.8.89)\n",
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"Requirement already satisfied: nvidia-cuda-runtime-cu11==11.8.89 in /opt/conda/lib/python3.11/site-packages (from torch>=1.10.0->accelerate) (11.8.89)\n",
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"Requirement already satisfied: nvidia-cuda-cupti-cu11==11.8.87 in /opt/conda/lib/python3.11/site-packages (from torch>=1.10.0->accelerate) (11.8.87)\n",
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"Requirement already satisfied: nvidia-cudnn-cu11==8.7.0.84 in /opt/conda/lib/python3.11/site-packages (from torch>=1.10.0->accelerate) (8.7.0.84)\n",
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"Requirement already satisfied: nvidia-cublas-cu11==11.11.3.6 in /opt/conda/lib/python3.11/site-packages (from torch>=1.10.0->accelerate) (11.11.3.6)\n",
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"Requirement already satisfied: nvidia-cufft-cu11==10.9.0.58 in /opt/conda/lib/python3.11/site-packages (from torch>=1.10.0->accelerate) (10.9.0.58)\n",
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"Requirement already satisfied: nvidia-curand-cu11==10.3.0.86 in /opt/conda/lib/python3.11/site-packages (from torch>=1.10.0->accelerate) (10.3.0.86)\n",
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"Requirement already satisfied: nvidia-cusolver-cu11==11.4.1.48 in /opt/conda/lib/python3.11/site-packages (from torch>=1.10.0->accelerate) (11.4.1.48)\n",
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"Requirement already satisfied: nvidia-cusparse-cu11==11.7.5.86 in /opt/conda/lib/python3.11/site-packages (from torch>=1.10.0->accelerate) (11.7.5.86)\n",
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"Requirement already satisfied: nvidia-nccl-cu11==2.20.5 in /opt/conda/lib/python3.11/site-packages (from torch>=1.10.0->accelerate) (2.20.5)\n",
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"Requirement already satisfied: nvidia-nvtx-cu11==11.8.86 in /opt/conda/lib/python3.11/site-packages (from torch>=1.10.0->accelerate) (11.8.86)\n",
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"Requirement already satisfied: triton==2.3.0 in /opt/conda/lib/python3.11/site-packages (from torch>=1.10.0->accelerate) (2.3.0)\n",
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"Requirement already satisfied: zipp>=0.5 in /opt/conda/lib/python3.11/site-packages (from importlib-metadata->diffusers) (3.17.0)\n",
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"Requirement already satisfied: charset-normalizer<4,>=2 in /opt/conda/lib/python3.11/site-packages (from requests->transformers) (3.3.2)\n",
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"Requirement already satisfied: idna<4,>=2.5 in /opt/conda/lib/python3.11/site-packages (from requests->transformers) (3.6)\n",
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"Requirement already satisfied: urllib3<3,>=1.21.1 in /opt/conda/lib/python3.11/site-packages (from requests->transformers) (2.2.0)\n",
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"Requirement already satisfied: certifi>=2017.4.17 in /opt/conda/lib/python3.11/site-packages (from requests->transformers) (2024.2.2)\n",
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"Requirement already satisfied: parso<0.9.0,>=0.8.3 in /opt/conda/lib/python3.11/site-packages (from jedi>=0.16->ipython>=6.1.0->ipywidgets) (0.8.3)\n",
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"Requirement already satisfied: ptyprocess>=0.5 in /opt/conda/lib/python3.11/site-packages (from pexpect>4.3->ipython>=6.1.0->ipywidgets) (0.7.0)\n",
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"Requirement already satisfied: wcwidth in /opt/conda/lib/python3.11/site-packages (from prompt-toolkit<3.1.0,>=3.0.41->ipython>=6.1.0->ipywidgets) (0.2.13)\n",
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"Requirement already satisfied: MarkupSafe>=2.0 in /opt/conda/lib/python3.11/site-packages (from jinja2->torch>=1.10.0->accelerate) (2.1.5)\n",
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"Requirement already satisfied: executing>=1.2.0 in /opt/conda/lib/python3.11/site-packages (from stack-data->ipython>=6.1.0->ipywidgets) (2.0.1)\n",
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"Requirement already satisfied: asttokens>=2.1.0 in /opt/conda/lib/python3.11/site-packages (from stack-data->ipython>=6.1.0->ipywidgets) (2.4.1)\n",
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"Requirement already satisfied: pure-eval in /opt/conda/lib/python3.11/site-packages (from stack-data->ipython>=6.1.0->ipywidgets) (0.2.2)\n",
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"Requirement already satisfied: mpmath>=0.19 in /opt/conda/lib/python3.11/site-packages (from sympy->torch>=1.10.0->accelerate) (1.3.0)\n",
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"Requirement already satisfied: six>=1.12.0 in /opt/conda/lib/python3.11/site-packages (from asttokens>=2.1.0->stack-data->ipython>=6.1.0->ipywidgets) (1.16.0)\n",
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"Downloading transformers-4.45.0-py3-none-any.whl (9.9 MB)\n",
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"\u001b[2K \u001b[90m━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[32m9.9/9.9 MB\u001b[0m \u001b[31m45.4 MB/s\u001b[0m eta \u001b[36m0:00:00\u001b[0m00:01\u001b[0m00:01\u001b[0m\n",
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"\u001b[?25hDownloading diffusers-0.30.3-py3-none-any.whl (2.7 MB)\n",
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"\u001b[2K \u001b[90m━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[32m2.7/2.7 MB\u001b[0m \u001b[31m44.9 MB/s\u001b[0m eta \u001b[36m0:00:00\u001b[0ma \u001b[36m0:00:01\u001b[0m\n",
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"\u001b[?25hDownloading accelerate-0.34.2-py3-none-any.whl (324 kB)\n",
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"\u001b[2K \u001b[90m━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[32m324.4/324.4 kB\u001b[0m \u001b[31m31.0 MB/s\u001b[0m eta \u001b[36m0:00:00\u001b[0m\n",
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"\u001b[?25hDownloading huggingface_hub-0.25.1-py3-none-any.whl (436 kB)\n",
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"\u001b[2K \u001b[90m━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[32m436.4/436.4 kB\u001b[0m \u001b[31m37.6 MB/s\u001b[0m eta \u001b[36m0:00:00\u001b[0m\n",
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"\u001b[?25hDownloading regex-2024.9.11-cp311-cp311-manylinux_2_17_x86_64.manylinux2014_x86_64.whl (792 kB)\n",
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"\u001b[2K \u001b[90m━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[32m792.8/792.8 kB\u001b[0m \u001b[31m41.9 MB/s\u001b[0m eta \u001b[36m0:00:00\u001b[0m\n",
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"\u001b[?25hDownloading safetensors-0.4.5-cp311-cp311-manylinux_2_17_x86_64.manylinux2014_x86_64.whl (435 kB)\n",
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"\u001b[2K \u001b[90m━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[32m435.0/435.0 kB\u001b[0m \u001b[31m31.3 MB/s\u001b[0m eta \u001b[36m0:00:00\u001b[0m\n",
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"\u001b[?25hDownloading tokenizers-0.20.0-cp311-cp311-manylinux_2_17_x86_64.manylinux2014_x86_64.whl (2.9 MB)\n",
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"\u001b[2K \u001b[90m━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[32m2.9/2.9 MB\u001b[0m \u001b[31m52.9 MB/s\u001b[0m eta \u001b[36m0:00:00\u001b[0m:00:01\u001b[0m\n",
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"\u001b[?25hInstalling collected packages: safetensors, regex, huggingface-hub, tokenizers, diffusers, accelerate, transformers\n",
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"Successfully installed accelerate-0.34.2 diffusers-0.30.3 huggingface-hub-0.25.1 regex-2024.9.11 safetensors-0.4.5 tokenizers-0.20.0 transformers-4.45.0\n"
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]
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}
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],
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"source": [
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"!pip install transformers diffusers accelerate ipywidgets"
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]
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},
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{
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"cell_type": "code",
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"execution_count": 2,
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"id": "6814d202-9131-4170-a967-6527a504eff4",
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"metadata": {
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"tags": []
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},
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"outputs": [],
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"source": [
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"import torch\n",
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"from diffusers import StableDiffusionPipeline\n",
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"from matplotlib import pyplot as plt\n",
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"import datetime"
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]
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},
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{
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"cell_type": "code",
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"execution_count": 3,
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"id": "9a48b8ed-6f07-4f27-95eb-7ec45c4a7d2f",
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"metadata": {
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"tags": []
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},
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"outputs": [],
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"source": [
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"# diffusers docs: https://huggingface.co/docs/diffusers/api/pipelines/stable_diffusion/text2img#texttoimage-generation\n",
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"# model_id = \"dreamlike-art/dreamlike-diffusion-1.0\"\n",
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"# model_id = \"prompthero/openjourney\"\n",
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"# model_id = \"XpucT/Deliberate\"\n",
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"model_id = \"dreamlike-art/dreamlike-photoreal-2.0\""
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]
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},
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{
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"cell_type": "code",
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"execution_count": 4,
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"id": "895b7852-6e82-4d74-bada-4e5b92ef90f4",
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"metadata": {},
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"outputs": [
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{
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"data": {
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"application/vnd.jupyter.widget-view+json": {
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"model_id": "b635499e010a40d595430657db538a65",
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"version_major": 2,
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"version_minor": 0
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},
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"text/plain": [
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"Loading pipeline components...: 0%| | 0/5 [00:00<?, ?it/s]"
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]
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},
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"metadata": {},
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"output_type": "display_data"
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},
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{
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"name": "stderr",
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"output_type": "stream",
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"text": [
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"/opt/conda/lib/python3.11/site-packages/transformers/tokenization_utils_base.py:1617: FutureWarning: `clean_up_tokenization_spaces` was not set. It will be set to `True` by default. This behavior will be deprecated in transformers v4.45, and will be then set to `False` by default. For more details check this issue: https://github.com/huggingface/transformers/issues/31884\n",
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" warnings.warn(\n"
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]
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}
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],
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"source": [
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"pipe = StableDiffusionPipeline.from_pretrained(model_id, torch_dtype=torch.float16, safety_checker=None)\n",
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"device = \"cuda\" if torch.cuda.is_available() else \"mps\" if torch.backends.mps.is_available() else \"cpu\"\n",
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"pipe = pipe.to(device)"
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]
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},
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{
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"cell_type": "code",
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"execution_count": 5,
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"id": "2b343ab6-7c44-4a19-a4ee-e5cf24dc60ca",
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"metadata": {},
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"outputs": [
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{
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"data": {
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"application/vnd.jupyter.widget-view+json": {
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"model_id": "8dd6786c47864084bb8ae04d925851ec",
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"version_major": 2,
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"version_minor": 0
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},
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"text/plain": [
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"VBox(children=(Textarea(value='', layout=Layout(height='50px', width='auto'), placeholder='cats, sharks, ships…"
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]
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},
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"execution_count": 5,
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"metadata": {},
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"output_type": "execute_result"
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},
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{
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"data": {
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"text/plain": [
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"<Figure size 160x160 with 0 Axes>"
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]
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},
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"metadata": {},
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"output_type": "display_data"
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}
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],
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"source": [
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"import numpy as np\n",
|
||||
"import ipywidgets as widgets\n",
|
||||
"from IPython.display import clear_output, display\n",
|
||||
"\n",
|
||||
"import matplotlib.pyplot as plt\n",
|
||||
"from IPython.display import set_matplotlib_formats\n",
|
||||
"%matplotlib inline\n",
|
||||
"#set_matplotlib_formats('svg')\n",
|
||||
"\n",
|
||||
"np.random.seed(42)\n",
|
||||
"\n",
|
||||
"#prompt = \"Renaissance-style portrait of an astronaut in space, detailed starry background, reflective helmet, matte painting, hyperdetailed, CGSociety\"\n",
|
||||
"#negative_prompt = \"gold\"\n",
|
||||
"#textarea\n",
|
||||
"std_layout = widgets.Layout(width=\"auto\")\n",
|
||||
"\n",
|
||||
"prompt_box = widgets.Textarea(value='', placeholder='cats, sharks, ships, underwater, cinematic composition', description='', layout=widgets.Layout(height=\"50px\", width=\"auto\"))\n",
|
||||
"neg_prompt_box = widgets.Textarea(value='', placeholder='negative prompt', description='', layout=widgets.Layout(height=\"30px\", width=\"auto\"))\n",
|
||||
"#slider \n",
|
||||
"img2gen_lab = widgets.Label(value=\"Images to Generate:\", layout=std_layout)\n",
|
||||
"img2gen_var = widgets.IntSlider(value=1, min=1, max=10, layout=std_layout)\n",
|
||||
"#input\n",
|
||||
"size_x_lab = widgets.Label(value=\"Image Width:\", layout=std_layout)\n",
|
||||
"size_x_var = widgets.BoundedIntText(value=32, min=32, max=512, step=8, layout=std_layout)\n",
|
||||
"size_y_lab = widgets.Label(value=\"Image heigth:\", layout=std_layout)\n",
|
||||
"size_y_var = widgets.BoundedIntText(value=32, min=32, max=512, step=8, layout=std_layout)\n",
|
||||
"steps_lab = widgets.Label(value=\"Steps:\", layout=std_layout)\n",
|
||||
"steps_var = widgets.BoundedIntText(value=50, min=11, max=100, step=1, layout=std_layout)\n",
|
||||
"#Button\n",
|
||||
"btn = widgets.Button(description=\"Generate\", tooltip=\"Click me\",\n",
|
||||
" layout=widgets.Layout(width=\"auto\", height=\"30px\", margin=\"30px\"))\n",
|
||||
"#Canvas\n",
|
||||
"fig = plt.figure(figsize=(128/80, 128/80))\n",
|
||||
"box = widgets.VBox([prompt_box, neg_prompt_box, img2gen_lab, img2gen_var, steps_lab, steps_var, size_x_lab, size_x_var,size_y_lab, size_y_var, btn])\n",
|
||||
"box2 = widgets.VBox([prompt_box, neg_prompt_box, img2gen_lab, img2gen_var, steps_lab, steps_var, size_x_lab, size_x_var,size_y_lab, size_y_var, btn])\n",
|
||||
"\n",
|
||||
"box2"
|
||||
]
|
||||
},
|
||||
{
|
||||
"cell_type": "code",
|
||||
"execution_count": 6,
|
||||
"id": "71055e73-a072-41d7-84c6-602fa69ff46f",
|
||||
"metadata": {},
|
||||
"outputs": [
|
||||
{
|
||||
"data": {
|
||||
"application/vnd.jupyter.widget-view+json": {
|
||||
"model_id": "4ada6ef0af1647a094013dbbc578e8ec",
|
||||
"version_major": 2,
|
||||
"version_minor": 0
|
||||
},
|
||||
"text/plain": [
|
||||
"Output()"
|
||||
]
|
||||
},
|
||||
"execution_count": 6,
|
||||
"metadata": {},
|
||||
"output_type": "execute_result"
|
||||
}
|
||||
],
|
||||
"source": [
|
||||
"out = widgets.Output()\n",
|
||||
"out"
|
||||
]
|
||||
},
|
||||
{
|
||||
"cell_type": "code",
|
||||
"execution_count": 7,
|
||||
"id": "d2645fdf-4bed-43f1-b3d1-f06c174d45ad",
|
||||
"metadata": {},
|
||||
"outputs": [],
|
||||
"source": [
|
||||
"def on_value_change(change):\n",
|
||||
" prompt = prompt_box.value\n",
|
||||
" negative_prompt = neg_prompt_box.value\n",
|
||||
" images_to_generate = int(img2gen_var.value)\n",
|
||||
" steps = steps_var.value\n",
|
||||
" width = size_x_var.value\n",
|
||||
" height = size_y_var.value\n",
|
||||
" seed = None\n",
|
||||
" guidance = 7.5 # Higher guidance scale encourages to generate images that are closely linked to the text prompt, usually at the expense of lower image quality.\n",
|
||||
" with out:\n",
|
||||
" clear_output(wait=True)\n",
|
||||
" for _ in range(images_to_generate):\n",
|
||||
" steps = int(steps)\n",
|
||||
" width = int(width)\n",
|
||||
" height = int(height)\n",
|
||||
" current_seed = seed or torch.randint(0, int(1e5), size=(1, 1))[0].item()\n",
|
||||
" generator = torch.Generator().manual_seed(int(current_seed))\n",
|
||||
" img = pipe(prompt=prompt, negative_prompt=negative_prompt, width=width, height=height, num_inference_steps=steps, guidance_scale=guidance, generator=generator).images[0]\n",
|
||||
" time_now = datetime.datetime.now().strftime(\"%y.%m.%d_%H:%M:%S\")\n",
|
||||
" plt.imshow(img)\n",
|
||||
" plt.axis(\"off\")\n",
|
||||
" print(\"Current Seed:\", current_seed)\n",
|
||||
" plt.title(\"\")\n",
|
||||
" plt.show()\n",
|
||||
" # img.save(f\"./{time_now}_{current_seed}.jpg\")\n",
|
||||
"\n",
|
||||
"btn.on_click(on_value_change)\n",
|
||||
"\n"
|
||||
]
|
||||
},
|
||||
{
|
||||
"cell_type": "code",
|
||||
"execution_count": null,
|
||||
"id": "801c01c7-d364-411a-ba10-25161e47f65f",
|
||||
"metadata": {},
|
||||
"outputs": [],
|
||||
"source": []
|
||||
}
|
||||
],
|
||||
"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": "3.11.7"
|
||||
}
|
||||
},
|
||||
"nbformat": 4,
|
||||
"nbformat_minor": 5
|
||||
}
|
||||
Loading…
Reference in New Issue