Instructions to use ChatterjeeLab/MetaLATTE with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use ChatterjeeLab/MetaLATTE with Transformers:
# Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("ChatterjeeLab/MetaLATTE", dtype="auto") - Notebooks
- Google Colab
- Kaggle
Commit ·
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Parent(s): 935f2f3
update
Browse files
README.md
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@@ -28,9 +28,10 @@ import sys
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from transformers import AutoTokenizer, AutoModel, AutoConfig
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metalatte_path = './Chatterjeelab/MetaLATTE'
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sys.path.insert(0, metalatte_path)
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from metalatte import MetaLATTEConfig,
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AutoConfig.register("metalatte", MetaLATTEConfig)
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AutoModel.register(MetaLATTEConfig,
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tokenizer = AutoTokenizer.from_pretrained("facebook/esm2_t33_650M_UR50D")
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config = AutoConfig.from_pretrained("ChatterjeeLab/MetaLATTE")
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from transformers import AutoTokenizer, AutoModel, AutoConfig
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metalatte_path = './Chatterjeelab/MetaLATTE'
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sys.path.insert(0, metalatte_path)
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from metalatte import MetaLATTEConfig, MultitaskProteinModel
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AutoConfig.register("metalatte", MetaLATTEConfig)
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AutoModel.register(MetaLATTEConfig, MultitaskProteinModel)
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tokenizer = AutoTokenizer.from_pretrained("facebook/esm2_t33_650M_UR50D")
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config = AutoConfig.from_pretrained("ChatterjeeLab/MetaLATTE")
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