Instructions to use WALIDALI/hallachillout with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use WALIDALI/hallachillout with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("WALIDALI/hallachillout", 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 WALIDALI/hallachillout: direct link, hf CLI and curl.
- Browser
- Download file 246 MB
-
https://huggingface.co/WALIDALI/hallachillout/resolve/main/text_encoder/pytorch_model.bin
- Command line
-
hf download hf://WALIDALI/hallachillout/text_encoder/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/WALIDALI/hallachillout/resolve/main/text_encoder/pytorch_model.bin
246 MB
- Xet hash:
- df53eeea52f7eb6f9a23512cae35dfd817241117f3193ea935b69965bfa1a3bd
- Size of remote file:
- 246 MB
- SHA256:
- 29c63506b6a3d8361386a580a194a6c03be32e1e06ebb4858486f9106bf43037
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