Instructions to use ByteDance/Bernini-Diffusers with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use ByteDance/Bernini-Diffusers with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("ByteDance/Bernini-Diffusers", 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
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README.md
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<h4 align="center">Latent Semantic Planning for Video Diffusion</h4>
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<img src="assets/bernini-icon.png" width="560" alt="Bernini"/>
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<h4 align="center">Latent Semantic Planning for Video Diffusion</h4>
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