Instructions to use YaronElh/CCSR-v2 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use YaronElh/CCSR-v2 with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("YaronElh/CCSR-v2", dtype=torch.bfloat16, device_map="cuda") prompt = "Astronaut in a jungle, cold color palette, muted colors, detailed, 8k" image = pipe(prompt).images[0] - Notebooks
- Google Colab
- Kaggle
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Check out the documentation for more information.
(Draft v1)
Download the pretrained SD-2.1-base models from HuggingFace. https://huggingface.co/stabilityai/stable-diffusion-2-1-base/resolve/main/v2-1_512-ema-pruned.ckpt
https://github.com/csslc/CCSR/issues/30#issuecomment-2314607165
CUDA version 12.5. conda install pytorch==2.3.1 torchvision==0.18.1 torchaudio==2.3.1 pytorch-cuda=12.1 -c pytorch -c nvidia export CUDA_HOME=/usr/local/cuda-12.5 export PATH=$CUDA_HOME/bin:$PATH export LD_LIBRARY_PATH=$CUDA_HOME/lib64:$LD_LIBRARY_PATH
https://github.com/csslc/CCSR/issues/41#issuecomment-2553300085 Hello, the --pretrained_model_path sholud be preset/models/stable-diffusion-2-1-base, which you can download from HuggingFace.
Reupload of models from https://github.com/csslc/CCSR/tree/CCSR-v2.0
Maintaining original project license: apache-2.0
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