Instructions to use ermu2001/ChatAnything with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use ermu2001/ChatAnything with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("ermu2001/ChatAnything", 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 MODELS/Face-Landmark-ControlNet/models_for_diffusers/diffusion_pytorch_model.bin from ermu2001/ChatAnything: direct link, hf CLI and curl.
- Browser
- Download file 1.45 GB
-
https://huggingface.co/ermu2001/ChatAnything/resolve/bcd8ff32eef43e5f6d908ebfaafa947cd600b2da/MODELS/Face-Landmark-ControlNet/models_for_diffusers/diffusion_pytorch_model.bin
- Command line
-
hf download hf://ermu2001/ChatAnything@bcd8ff32eef43e5f6d908ebfaafa947cd600b2da/MODELS/Face-Landmark-ControlNet/models_for_diffusers/diffusion_pytorch_model.bin
-
curl -L -o diffusion_pytorch_model.bin https://huggingface.co/ermu2001/ChatAnything/resolve/bcd8ff32eef43e5f6d908ebfaafa947cd600b2da/MODELS/Face-Landmark-ControlNet/models_for_diffusers/diffusion_pytorch_model.bin
1.45 GB
- Xet hash:
- cf9dbc3c983181d91cfbbc8785aec3a20c12509e58edf150bb6109439d459333
- Size of remote file:
- 1.45 GB
- SHA256:
- 98bcc648449f9e596496e3f826412f6e0cfed8340ad97b146e1c5991d5eeddfb
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