Instructions to use recursionpharma/OpenPhenom with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use recursionpharma/OpenPhenom with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("feature-extraction", model="recursionpharma/OpenPhenom", trust_remote_code=True)# Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("recursionpharma/OpenPhenom", trust_remote_code=True, dtype="auto") - Notebooks
- Google Colab
- Kaggle
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README.md
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## Provided models
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A publicly available model for research can be found via Nvidia's BioNemo platform, which handles inference and auto-scaling for you: https://www.rxrx.ai/phenom
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## Provided models
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A publicly available model for research can be found via Nvidia's BioNemo platform, which handles inference and auto-scaling for you: https://www.rxrx.ai/phenom
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We have partnered with Nvidia to host a publicly-available smaller and more flexible version of the MAE phenomics foundation model, called Phenom-Beta. Interested parties can access it directly through the Nvidia BioNemo API:
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- https://blogs.nvidia.com/blog/drug-discovery-bionemo-generative-ai/
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- https://www.youtube.com/watch?v=Gch6bX1toB0
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