Diffusers
Safetensors
English
RFD4ProteinaPipeline
biology
protein-design
biomolecular-design
structure-generation
flow-matching
annotated-cif
Instructions to use nvidia/RFD4-Proteina-Diffusers with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use nvidia/RFD4-Proteina-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("nvidia/RFD4-Proteina-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
Install Diffusers from git until the release carries RFD4-Proteina
Browse filesRFD4-Proteina was merged into Diffusers upstream as huggingface/diffusers#15088 on 2026-10-20, so the pipeline no longer comes from a staging branch. It is not on PyPI yet, which the next Diffusers release fixes, so the quickstart installs from git and shows the plain pip line commented out beside it.
Checked rather than assumed, in a clean 3.12 environment: the git install imports RFD4ProteinaPipeline, and nvidia/RFD4-Proteina-Diffusers loads through it with all four components and no newly-initialized warnings. accelerate is listed because the load fails without it: "`low_cpu_mem_usage` cannot be False when `keep_in_fp32_modules` is True".
README.md
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## Quickstart
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```bash
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```
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```python
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## Quickstart
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```bash
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# RFD4-Proteina was merged into Diffusers on 2026-10-20 and ships in the next release.
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# Until that release, install Diffusers from git:
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pip install git+https://github.com/huggingface/diffusers git+https://huggingface.co/nvidia/RFD4-Proteina-prep@c9959efdebd75ac7fe9129fbbf0e291a6e0487d5 accelerate
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# Once the release is out, this is enough:
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# pip install diffusers git+https://huggingface.co/nvidia/RFD4-Proteina-prep@c9959efdebd75ac7fe9129fbbf0e291a6e0487d5
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```
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```python
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