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
Download modular_model_index.json from nvidia/RFD4-Proteina-prep: direct link, hf CLI and curl.
- Browser
- Download file 119 Bytes
-
https://huggingface.co/nvidia/RFD4-Proteina-prep/resolve/main/modular_model_index.json
- Command line
-
hf download hf://nvidia/RFD4-Proteina-prep/modular_model_index.json
-
curl -L -o modular_model_index.json https://huggingface.co/nvidia/RFD4-Proteina-prep/resolve/main/modular_model_index.json
119 Bytes
| { | |
| "_blocks_class_name": "RFD4CIFBlocks", | |
| "_class_name": "ModularPipeline", | |
| "_diffusers_version": "0.41.0.dev0" | |
| } | |