Instructions to use XPeng2022/hgs3 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use XPeng2022/hgs3 with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("XPeng2022/hgs3", 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 text_encoder/pytorch_model.bin from XPeng2022/hgs3: direct link, hf CLI and curl.
- Browser
- Download file 246 MB
-
https://huggingface.co/XPeng2022/hgs3/resolve/main/text_encoder/pytorch_model.bin
- Command line
-
hf download hf://XPeng2022/hgs3/text_encoder/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/XPeng2022/hgs3/resolve/main/text_encoder/pytorch_model.bin
246 MB
- Xet hash:
- e893044821757dcbd7f54652293690be4ec40f210b265cda0c867f84b79c6384
- Size of remote file:
- 246 MB
- SHA256:
- 4a673f460534d17bf906cc0e17d235cdc93c47d4e8c75417f79ae6e2524e21f9
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