Instructions to use budecosystem/Chhavi with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use budecosystem/Chhavi with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("budecosystem/Chhavi", 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 unet/diffusion_pytorch_model.safetensors from budecosystem/Chhavi: direct link, hf CLI and curl.
- Browser
- Download file 5.14 GB
-
https://huggingface.co/budecosystem/Chhavi/resolve/main/unet/diffusion_pytorch_model.safetensors
- Command line
-
hf download hf://budecosystem/Chhavi/unet/diffusion_pytorch_model.safetensors
-
curl -L -o diffusion_pytorch_model.safetensors https://huggingface.co/budecosystem/Chhavi/resolve/main/unet/diffusion_pytorch_model.safetensors
5.14 GB
- Xet hash:
- a13f858f73da7c8aad618232a52a1ea92a76db43781ee86ce3e4f1399e128c37
- Size of remote file:
- 5.14 GB
- SHA256:
- ebd8bc0b51eabb6564c3caa42a089eca16e9f9ab6753fd8eed61f6b8705bb1df
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