Instructions to use dn6/RosettaFold-3 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use dn6/RosettaFold-3 with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("dn6/RosettaFold-3", torch_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
| # Copyright 2025 Dhruv Nair. All rights reserved. | |
| # Licensed under the Apache License, Version 2.0 | |
| from .transformer import RF3TransformerModel, RF3TransformerOutput | |
| from .scheduler import RF3Scheduler | |
| from .modular_blocks import ( | |
| RF3AutoBeforeDenoiseStep, | |
| RF3AutoBlocks, | |
| RF3AutoDecodeStep, | |
| RF3AutoDenoiseStep, | |
| ) | |
| from .before_denoise import ( | |
| RF3InputStep, | |
| RF3PrepareLatentsStep, | |
| RF3RecyclingStep, | |
| RF3SetTimestepsStep, | |
| ) | |
| from .denoise import RF3DenoiseStep | |
| from .decoders import RF3DecodeStep, RF3PipelineOutput | |