Instructions to use QinmingZhou/OSOR with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use QinmingZhou/OSOR with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("fill-in-base-model", torch_dtype=torch.bfloat16, device_map="cuda") pipe.load_lora_weights("QinmingZhou/OSOR") prompt = "Astronaut in a jungle, cold color palette, muted colors, detailed, 8k" image = pipe(prompt).images[0] - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- Draw Things
Add OSOR FLUX-Fill checkpoints
Browse files
osor-fluxfill/weights/fluxfill_phase1.pth
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version https://git-lfs.github.com/spec/v1
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oid sha256:3574454495a7230f34be0242aaa199879bb2ed33ae686868054584cd9c4b8878
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size 598679636
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osor-fluxfill/weights/fluxfill_phase2.pth
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version https://git-lfs.github.com/spec/v1
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oid sha256:de3d70b35b48ca1529954474e315a3c3b3b6fb22318bfbc1853b3a61d223b307
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size 598728788
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