Instructions to use nvidia/RFD4-Proteina-prep with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use nvidia/RFD4-Proteina-prep 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-prep", 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
Commit History
4 days ago
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Skip the custom-block test when diffusers is absent
`pytest` failed at collection for anyone who installed this package and its documented test extra and nothing else: tests/test_custom_block.py imports `diffusers` at module scope, and `diffusers` is not a dependency here -- the `test` extra is pytest alone. The failure is a collection error, so it took the whole suite down with it rather than just that file. `pytest.importorskip("diffusers")` before the import, which is what test_prepare.py already does for `atomworks`. Behaviour is unchanged wherever diffusers is installed; where it is not, the module skips and the rest of the suite runs. Verified against a wheel built from this repository and installed without diffusers: 2 passed, 1 skipped, where it was previously 1 error. Declaring diffusers in the test extra would also work, but it would make the package's own tests pull the library that depends on it, so skipping is the lighter answer. Co-Authored-By: Claude Opus 5 <noreply@anthropic.com>040b0b2 -
Add modular CIF helper and non-antibody Studio input catalog
Verified signatureAdditive helper, pinned example runner and CPU tests. Existing preprocessing source, model weights and repository visibility are unchanged.5ab5b72