Buckets:
| import torch | |
| from diffusers import FluxFillPipeline | |
| from diffusers.utils import load_image | |
| from nunchaku import NunchakuFluxTransformer2dModel | |
| from nunchaku.utils import get_precision | |
| image = load_image("https://huggingface.co/datasets/diffusers/diffusers-images-docs/resolve/main/cup.png") | |
| mask = load_image("https://huggingface.co/datasets/diffusers/diffusers-images-docs/resolve/main/cup_mask.png") | |
| precision = get_precision() # auto-detect your precision is 'int4' or 'fp4' based on your GPU | |
| transformer = NunchakuFluxTransformer2dModel.from_pretrained( | |
| f"nunchaku-tech/nunchaku-flux.1-fill-dev/svdq-{precision}_r32-flux.1-fill-dev.safetensors" | |
| ) | |
| pipe = FluxFillPipeline.from_pretrained( | |
| "black-forest-labs/FLUX.1-Fill-dev", transformer=transformer, torch_dtype=torch.bfloat16 | |
| ).to("cuda") | |
| image = pipe( | |
| prompt="a white paper cup", | |
| image=image, | |
| mask_image=mask, | |
| height=1024, | |
| width=1024, | |
| guidance_scale=30, | |
| num_inference_steps=50, | |
| max_sequence_length=512, | |
| ).images[0] | |
| image.save(f"flux.1-fill-dev-{precision}.png") | |
Xet Storage Details
- Size:
- 1.06 kB
- Xet hash:
- 161bdf746a8cc69f2e4032999be27623dd35d60214133c7b03effe284442a87a
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