Instructions to use hjgp/inpaint with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use hjgp/inpaint with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("hjgp/inpaint", 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
- Local Apps Settings
- Draw Things
- DiffusionBee
- Xet hash:
- da670b406d940a5e29a584749ada2136e48426cee86330c8c0bdf2d7065bae53
- Size of remote file:
- 492 MB
- SHA256:
- 76d15135d25c6c69b6a1e213f40b32b4ed4ac40c6512ea7a01ea2132d7f94324
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