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
Update config.json
Browse files- config.json +4 -0
config.json
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{
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"_attn_implementation_autoset": true,
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"apply_loss_unmasked": false,
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"architectures": [
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"MAEModel"
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{
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"_attn_implementation_autoset": true,
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"auto_map": {
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"AutoModel": "huggingface_mae.MAEModel",
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"AutoConfig": "huggingface_mae.MAEConfig"
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},
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"apply_loss_unmasked": false,
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"architectures": [
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"MAEModel"
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