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-20000/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-20000/optimizer.bin
- Command line
-
hf download hf://22Plaruno/face_generation_/checkpoint-20000/optimizer.bin
-
curl -L -o optimizer.bin https://huggingface.co/22Plaruno/face_generation_/resolve/main/checkpoint-20000/optimizer.bin
910 MB
- Xet hash:
- 01f39572682b42f71c08e9f447e05cba77abe03f896c782e440feeb1ce3a1888
- Size of remote file:
- 910 MB
- SHA256:
- 0b052f958ae36a791d54dfd3e9e2c0d576b6dde40dd0460ae53c0c182c0f8f90
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