Instructions to use feishen29/IMAGDressing with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use feishen29/IMAGDressing with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("feishen29/IMAGDressing", 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
Download image_encoder/pytorch_model.bin from feishen29/IMAGDressing: direct link, hf CLI and curl.
- Browser
- Download file 2.53 GB
-
https://huggingface.co/feishen29/IMAGDressing/resolve/refs%2Fpr%2F1/image_encoder/pytorch_model.bin
- Command line
-
hf download hf://feishen29/IMAGDressing@refs/pr/1/image_encoder/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/feishen29/IMAGDressing/resolve/refs%2Fpr%2F1/image_encoder/pytorch_model.bin
2.53 GB
- Xet hash:
- 7f4f485bc586db4b718603ccc6294d9505843b5317fe04ea1084bbd2353e18d9
- Size of remote file:
- 2.53 GB
- SHA256:
- 3d3ec1e66737f77a4f3bc2df3c52eacefc69ce7825e2784183b1d4e9877d9193
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