Instructions to use 22Plaruno/face_generation_ with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use 22Plaruno/face_generation_ with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("22Plaruno/face_generation_", 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 checkpoint-16000/optimizer.bin from 22Plaruno/face_generation_: direct link, hf CLI and curl.
- Browser
- Download file 910 MB
-
https://huggingface.co/22Plaruno/face_generation_/resolve/main/checkpoint-16000/optimizer.bin
- Command line
-
hf download hf://22Plaruno/face_generation_/checkpoint-16000/optimizer.bin
-
curl -L -o optimizer.bin https://huggingface.co/22Plaruno/face_generation_/resolve/main/checkpoint-16000/optimizer.bin
910 MB
- Xet hash:
- cc8edc28e13e024f148c7d67c2c17f4ce0c442d2f8e99d284b27cf2a30b4b56f
- Size of remote file:
- 910 MB
- SHA256:
- a0960ef4f1c3240e855f847ea9cf664b997fb1eb84d6968b0b235b9dabe87212
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