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, device_map="auto")# Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("recursionpharma/OpenPhenom", trust_remote_code=True, dtype="auto", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 7646f4a9c1e2e8f062ebd5ce9f5804b683771659c443476807b0396aeefa59d9
- Size of remote file:
- 712 MB
- SHA256:
- e1f1ad069f4478524c55525ed4c19f9eb82b0ea9a44995c87b312991f9ad9473
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