Instructions to use fal/Bernini-R-Aux-FlashPack with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use fal/Bernini-R-Aux-FlashPack with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("fal/Bernini-R-Aux-FlashPack", 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
Commit History
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FlashPack conversion manifest for ByteDance/Bernini-R-Diffusers@de8c4621d3ac75cc33efe3db8deaed2023e9ac8c
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Add files using upload-large-folder tool
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Remove stale files superseded by new FlashPack conversion
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initial commit
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