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ProTrek_35M

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@@ -10,11 +10,11 @@ During the pre-training phase, we calculate the InfoNCE loss for each two modali
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  ## Model architecture
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- Protein sequence encoder: [esm2_t12_35M_UR50D](https://huggingface.co/facebook/esm2_t12_35M_UR50D)
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- Protein structure encoder: foldseek_t12_35M (identical architecture with esm2 except that the vocabulary only contains 3Di tokens)
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- Text encoder: [BiomedNLP-PubMedBERT-base-uncased-abstract-fulltext](https://huggingface.co/microsoft/BiomedNLP-BiomedBERT-base-uncased-abstract-fulltext)
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  ## Obtain embeddings and calculate similarity score (please clone our repo first)
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  ```
 
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  does.
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  ## Model architecture
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+ **Protein sequence encoder**: [esm2_t12_35M_UR50D](https://huggingface.co/facebook/esm2_t12_35M_UR50D)
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+ **Protein structure encoder**: foldseek_t12_35M (identical architecture with esm2 except that the vocabulary only contains 3Di tokens)
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+ **Text encoder**: [BiomedNLP-PubMedBERT-base-uncased-abstract-fulltext](https://huggingface.co/microsoft/BiomedNLP-BiomedBERT-base-uncased-abstract-fulltext)
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  ## Obtain embeddings and calculate similarity score (please clone our repo first)
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  ```