Instructions to use wxcvbnw/havrans with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use wxcvbnw/havrans with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("wxcvbnw/havrans", 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 wxcvbnw/havrans: direct link, hf CLI and curl.
- Browser
- Download file 681 MB
-
https://huggingface.co/wxcvbnw/havrans/resolve/main/text_encoder/pytorch_model.bin
- Command line
-
hf download hf://wxcvbnw/havrans/text_encoder/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/wxcvbnw/havrans/resolve/main/text_encoder/pytorch_model.bin
681 MB
- Xet hash:
- 29c97f71452aca27fbe48c0dd154965ed2149f7a4451c28812f7ad5a454dc1bd
- Size of remote file:
- 681 MB
- SHA256:
- 812596c0d62e27e22044ab9e1c41537fed3fe1d8986847c3d2efca5bea8c31df
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