Instructions to use R-J/StainFuser with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use R-J/StainFuser with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("R-J/StainFuser", 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
UPD: upload model checkpoints
Browse files- checkpoint.pth +3 -0
- checkpoint.safetensors +3 -0
checkpoint.pth
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version https://git-lfs.github.com/spec/v1
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oid sha256:90b5e1b9909126c4f014f86820c56fd3470c3ea9ab218dc0e15babc17d2918a7
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size 5255669366
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checkpoint.safetensors
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version https://git-lfs.github.com/spec/v1
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oid sha256:e95b11f82e9593aeddd5ca2f6eae1df3c012f9d31f372089f909abb90b5f14a1
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size 5255383188
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