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
- Xet hash:
- dd3bfc41f64e9f76004195a9ce4ec450d360a94b084fa1df2401cf5670f96cda
- Size of remote file:
- 712 MB
- SHA256:
- f6e5f1c97101331b1574c9e4b99623260191c55eea5d98e40460849c0e4c4d47
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