Instructions to use osanseviero/huggingface2 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use osanseviero/huggingface2 with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("osanseviero/huggingface2", 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 safety_checker/pytorch_model.bin from osanseviero/huggingface2: direct link, hf CLI and curl.
- Browser
- Download file 1.22 GB
-
https://huggingface.co/osanseviero/huggingface2/resolve/main/safety_checker/pytorch_model.bin
- Command line
-
hf download hf://osanseviero/huggingface2/safety_checker/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/osanseviero/huggingface2/resolve/main/safety_checker/pytorch_model.bin
1.22 GB
- Xet hash:
- 60dd6a051aea64d5bb1c3cfd426ad36dc953e48679c41de213a1eddd20ac8543
- Size of remote file:
- 1.22 GB
- SHA256:
- 193490b58ef62739077262e833bf091c66c29488058681ac25cf7df3d8190974
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