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
Upload model
Browse files- config.json +1 -1
config.json
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"pct_start": 0.1
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},
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"mask_fourier_loss": true,
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"mask_ratio": 0.
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"model_type": "MAE",
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"norm_pix_loss": false,
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"num_blocks_to_freeze": 0,
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"pct_start": 0.1
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},
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"mask_fourier_loss": true,
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"mask_ratio": 0.0,
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"model_type": "MAE",
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"norm_pix_loss": false,
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"num_blocks_to_freeze": 0,
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