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
File size: 653 Bytes
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"epoch": 4,
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"source_revision": "de8c4621d3ac75cc33efe3db8deaed2023e9ac8c",
"dtype": "keep",
"components": [
"text_encoder",
"vae"
],
"components_only": true,
"variant": null,
"include_root": false,
"ignore_names": [],
"ignore_prefixes": [],
"ignore_suffixes": [],
"files": null,
"pack_files": null,
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"script_sha256": "0d39c755c7e9476e2879cf63682143c06753a24dc3810ce489f25b25e1ad0586",
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} |