Text-to-Video
Diffusers
Safetensors
Wan2.2
bernini_renderer
comfyui
bernini-r
video-editing
reference-to-video
fp8
Instructions to use neuregex/Bernini-R-fp8 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use neuregex/Bernini-R-fp8 with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("neuregex/Bernini-R-fp8", dtype=torch.bfloat16, device_map="cuda") prompt = "Astronaut in a jungle, cold color palette, muted colors, detailed, 8k" image = pipe(prompt).images[0] - Wan2.2
How to use neuregex/Bernini-R-fp8 with Wan2.2:
# No code snippets available yet for this library. # To use this model, check the repository files and the library's documentation. # Want to help? PRs adding snippets are welcome at: # https://github.com/huggingface/huggingface.js
- Notebooks
- Google Colab
- Kaggle
- Xet hash:
- b0aa10500a7cf64010ade9068636f54784def3baeccd68d562c2b7de8a3ac995
- Size of remote file:
- 14.6 GB
- SHA256:
- b3fa68b48bc00c3750d76a059e38cd9016716fd780bc41f173b9a755390abc2c
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