Instructions to use admruul/hassan with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use admruul/hassan with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("admruul/hassan", 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 vae/diffusion_pytorch_model.bin from admruul/hassan: direct link, hf CLI and curl.
- Browser
- Download file 335 MB
-
https://huggingface.co/admruul/hassan/resolve/main/vae/diffusion_pytorch_model.bin
- Command line
-
hf download hf://admruul/hassan/vae/diffusion_pytorch_model.bin
-
curl -L -o diffusion_pytorch_model.bin https://huggingface.co/admruul/hassan/resolve/main/vae/diffusion_pytorch_model.bin
335 MB
- Xet hash:
- 181324361a38454da0f208ca05f1fed347c1fd09b79d16aac040dd257cbe95a1
- Size of remote file:
- 335 MB
- SHA256:
- 8b35db0323c11c073d28be039e178331d36efe1fd40f4a9d2dd68b74b62040b4
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.