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", 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: 546 Bytes
a376829 | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 | # 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
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