Instructions to use diffusers-modular/minimax-h3-inpainting with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use diffusers-modular/minimax-h3-inpainting with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("diffusers-modular/minimax-h3-inpainting", 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
Download assets/strip_example.webp from diffusers-modular/minimax-h3-inpainting: direct link, hf CLI and curl.
- Browser
- Download file 977 kB
-
https://huggingface.co/diffusers-modular/minimax-h3-inpainting/resolve/main/assets/strip_example.webp
- Command line
-
hf download hf://diffusers-modular/minimax-h3-inpainting/assets/strip_example.webp
-
curl -L -o strip_example.webp https://huggingface.co/diffusers-modular/minimax-h3-inpainting/resolve/main/assets/strip_example.webp
977 kB

- Xet hash:
- fc8a7ffe72cc029a4ac579b8b9f00a477ea2ae0d8f881bfed76b2d03a021569d
- Size of remote file:
- 977 kB
- SHA256:
- 7a21a145203d117e05d6bfe6254e04afbe8339e571b195fc66344fd416c8b0f3
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