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, device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- cf281fa7abef0533b799a7432e148c316b36712d7aeb80843a1dcab3b120b03c
- Size of remote file:
- 171 MB
- SHA256:
- af2bd54c39e670fba444ca08e0e223daf1a26394f26974259fd2d194e20bd5b7
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