Focus on prompting and generating
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liubomyr-lototskyi c216b4f748
Merge f82c6a7dc6 into ae05379cc9
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.github ci: bump actions/checkout from 4 to 5 (#4085) 2025-09-02 22:28:40 +02:00
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extras Use weights_only for loading (#3427) 2024-08-03 12:33:01 +02:00
javascript feat: revert adding detailed steps for each performance 2024-07-14 21:06:59 +02:00
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args_manager.py feat: sort enhance images (mashb1t#62) 2024-07-25 15:21:56 +02:00
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environment.yaml i 2023-08-10 03:55:55 -07:00
experiments_expansion.py [2.1.831] Fooocus Describe 2023-12-12 19:34:18 -08:00
experiments_face.py [2.1.831] Fooocus Describe 2023-12-12 19:34:18 -08:00
experiments_interrogate.py [2.1.831] Fooocus Describe 2023-12-12 19:34:18 -08:00
experiments_mask_generation.py Sync branch 'mashb1t_main' with develop_upstream 2024-07-14 20:28:38 +02:00
fooocus_colab.ipynb chore: update packages #2 2024-07-16 16:31:15 +02:00
fooocus_version.py release: bump version to 2.5.5, update changelog 2024-08-12 08:10:20 +02:00
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notification-example.mp3 feat: change example audio file 2024-07-16 13:59:51 +02:00
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run.bat Add files via upload 2025-11-23 17:47:46 +02:00
shared.py feat: advanced params refactoring + prevent users from skipping/stopping other users tasks in queue (#981) 2024-02-24 19:01:06 +01:00
update_log.md release: bump version to 2.5.5, update changelog 2024-08-12 08:10:20 +02:00
webui.py fix: change wrong label for in describe apply styles checkbox 2024-08-03 15:16:18 +02:00

readme.md

thx lllyasviel for a basic Fooocus version.

I noticed a rapidly growing trend where people are actively switching to RTX 5090, RTX 5070, 5080, etc., and suddenly realise that their familiar software does not work due to CUDA incompatibility.

This applies to stable-diffusion-webui, fooocus, and a number of other popular programmes. What to do in this situation? Install CUDA 12.8, install library versions that support it, such as torch nightly, and compile packages yourself if they do not yet have native support for the Broadwell generation (RTX 50xx).

What to do with portatives is more complicated.

After spending more than 20 hours testing different versions of CUDA, torch, torchvision, and various versions of wheels, I finally found a working setup.

Important: it works for me on RTX 5060TI 16GB, but I cannot guarantee that it will work on other 50x versions of NVIDIA.

Working combination: Python: 3.12.10

ONNXRuntime GPU: onnxruntime-gpu==1.22.0 (whl: onnxruntime_gpu-1.22.0-cp312-cp312-win_amd64.whl)

CUDA: 12.2

cuDNN: 8.9.x (also dll-s should be send at C:\Program Files\NVIDIA GPU Computing Toolkit\CUDA\v12.2\bin)

PATH written at bin and libnvvp CUDA

pip install torch==2.7.1+cu128 torchvision==0.22.1+cu128 torchaudio==2.7.1 --index-url https://download.pytorch.org/whl/cu128