mirror of
https://github.com/invoke-ai/InvokeAI
synced 2024-08-30 20:32:17 +00:00
266 lines
6.9 KiB
Plaintext
266 lines
6.9 KiB
Plaintext
{
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"cells": [
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{
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"cell_type": "markdown",
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"metadata": {},
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"source": [
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"# Easy-peasy Windows install"
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]
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},
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{
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"cell_type": "markdown",
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"metadata": {},
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"source": [
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"Note that you will need NVIDIA drivers, Python 3.10, and Git installed\n",
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"beforehand - simplified\n",
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"[step-by-step instructions](https://github.com/lstein/stable-diffusion/wiki/Easy-peasy-Windows-install)\n",
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"are available in the wiki (you'll only need steps 1, 2, & 3 )"
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]
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},
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{
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"cell_type": "markdown",
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"metadata": {},
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"source": [
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"### Run each cell in turn. In VSCode, either hit SHIFT-ENTER, or click on the little ▶️ to the left of the cell. In Jupyter/JupyterLab, you **must** hit SHIFT-ENTER"
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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": null,
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"metadata": {},
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"outputs": [],
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"source": [
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"%pip install pew"
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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": null,
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"metadata": {},
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"outputs": [],
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"source": [
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"%%cmd\n",
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"git clone https://github.com/lstein/stable-diffusion.git"
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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": null,
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"metadata": {},
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"outputs": [],
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"source": [
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"%cd stable-diffusion"
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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": null,
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"metadata": {},
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"outputs": [],
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"source": [
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"%%writefile requirements.txt\n",
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"albumentations==0.4.3\n",
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"einops==0.3.0\n",
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"huggingface-hub==0.8.1\n",
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"imageio-ffmpeg==0.4.2\n",
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"imageio==2.9.0\n",
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"kornia==0.6.0\n",
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"# pip will resolve the version which matches torch\n",
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"numpy\n",
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"omegaconf==2.1.1\n",
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"opencv-python==4.6.0.66\n",
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"pillow==9.2.0\n",
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"pip>=22\n",
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"pudb==2019.2\n",
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"pytorch-lightning==1.4.2\n",
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"streamlit==1.12.0\n",
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"# \"CompVis/taming-transformers\" doesn't work\n",
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"# ldm\\models\\autoencoder.py\", line 6, in <module>\n",
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"# from taming.modules.vqvae.quantize import VectorQuantizer2 as VectorQuantizer\n",
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"# ModuleNotFoundError\n",
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"taming-transformers-rom1504==0.0.6\n",
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"test-tube>=0.7.5\n",
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"torch-fidelity==0.3.0\n",
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"torchmetrics==0.6.0\n",
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"transformers==4.19.2\n",
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"git+https://github.com/openai/CLIP.git@main#egg=clip\n",
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"git+https://github.com/lstein/k-diffusion.git@master#egg=k-diffusion\n",
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"# No CUDA in PyPi builds\n",
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"--extra-index-url https://download.pytorch.org/whl/cu113 --trusted-host https://download.pytorch.org\n",
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"torch==1.11.0\n",
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"# Same as numpy - let pip do its thing\n",
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"torchvision\n",
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"-e .\n"
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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": null,
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"metadata": {},
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"outputs": [],
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"source": [
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"%%cmd\n",
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"pew new --python 3.10 -r requirements.txt --dont-activate ldm"
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]
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},
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{
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"cell_type": "markdown",
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"metadata": {},
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"source": [
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"# Switch the notebook kernel to the new 'ldm' environment!\n",
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"\n",
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"## VSCode: restart VSCode and come back to this cell\n",
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"\n",
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"1. Ctrl+Shift+P\n",
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"1. Type \"Select Interpreter\" and select \"Jupyter: Select Interpreter to Start Jupyter Server\"\n",
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"1. VSCode will say that it needs to install packages. Click the \"Install\" button.\n",
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"1. Once the install is finished, do 1 & 2 again\n",
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"1. Pick 'ldm'\n",
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"1. Run the following cell"
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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": null,
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"metadata": {},
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"outputs": [],
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"source": [
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"%cd stable-diffusion"
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]
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},
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{
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"cell_type": "markdown",
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"metadata": {},
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"source": [
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"\n",
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"## Jupyter/JupyterLab\n",
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"\n",
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"1. Run the cell below\n",
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"1. Click on the toolbar where it says \"(ipyknel)\" ↗️. You should get a pop-up asking you to \"Select Kernel\". Pick 'ldm' from the drop-down.\n"
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]
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},
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{
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"cell_type": "markdown",
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"metadata": {},
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"source": [
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"#### DO NOT RUN THE FOLLOWING CELL IF YOU ARE USING VSCODE!!"
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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": null,
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"metadata": {},
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"outputs": [],
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"source": [
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"# DO NOT RUN THIS CELL IF YOU ARE USING VSCODE!!\n",
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"%%cmd\n",
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"pew workon ldm\n",
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"pip3 install ipykernel\n",
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"python -m ipykernel install --name=ldm"
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]
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},
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{
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"cell_type": "markdown",
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"metadata": {},
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"source": [
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"#### When running the next cell, Jupyter/JupyterLab users might get a warning saying \"IProgress not found\". This can be ignored."
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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": null,
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"metadata": {},
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"outputs": [],
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"source": [
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"%run \"scripts/preload_models.py\""
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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": null,
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"metadata": {},
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"outputs": [],
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"source": [
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"%%cmd\n",
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"mkdir \"models/ldm/stable-diffusion-v1\""
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]
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},
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{
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"cell_type": "markdown",
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"metadata": {},
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"source": [
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"### Now copy the SD model you downloaded from Hugging Face into the above new directory, and (if necessary) rename it to 'model.ckpt'"
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]
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},
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{
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"cell_type": "markdown",
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"metadata": {},
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"source": [
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"### Now go create some magic!\n",
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"\n",
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"VSCode\n",
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"\n",
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"- The actual input box for the 'dream' prompt will appear at the very top of the VSCode window. Type in your commands and hit 'ENTER'.\n",
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"- To quit, hit the 'Interrupt' button in the toolbar up there ⬆️ a couple of times, then hit ENTER (you'll probably see a terrifying traceback from Python - just ignore it).\n",
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"\n",
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"Jupyter/JupyterLab\n",
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"\n",
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"- The input box for the 'dream' prompt will appear below. Type in your commands and hit 'ENTER'.\n",
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"- To quit, hit the interrupt button (⏹️) in the toolbar up there ⬆️ a couple of times, then hit ENTER (you'll probably see a terrifying traceback from Python - just ignore it)."
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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": null,
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"metadata": {},
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"outputs": [],
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"source": [
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"%run \"scripts/dream.py\""
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]
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},
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{
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"cell_type": "markdown",
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"metadata": {},
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"source": [
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"### Once this seems to be working well, you can try opening a terminal\n",
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"\n",
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"- VSCode: type ('CTRL+`')\n",
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"- Jupyter/JupyterLab: File|New Terminal\n",
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"- Or jump out of the notebook entirely, and open Powershell/Command Prompt\n",
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"\n",
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"Now:\n",
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"\n",
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"1. `cd` to wherever the 'stable-diffusion' directory is\n",
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"1. Run `pew workon ldm`\n",
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"1. Run `winpty python scripts\\dream.py`"
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]
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}
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],
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"metadata": {
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"kernelspec": {
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"display_name": "Python 3.10.6 ('ldm')",
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"language": "python",
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"name": "python3"
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},
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"language_info": {
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"codemirror_mode": {
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"name": "ipython",
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"version": 3
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},
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"file_extension": ".py",
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"mimetype": "text/x-python",
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"name": "python",
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"nbconvert_exporter": "python",
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"pygments_lexer": "ipython3",
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"version": "3.10.6"
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},
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"vscode": {
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"interpreter": {
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"hash": "a05e4574567b7bc2c98f7f9aa579f9ea5b8739b54844ab610ac85881c4be2659"
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}
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}
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},
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"nbformat": 4,
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"nbformat_minor": 4
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}
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