AmelieSchreiber/esm2_t12_35M_lora_binding_sites_v2_cp3

https://huggingface.co/AmelieSchreiber/esm2_t12_35M_lora_binding_sites_v2_cp3
Staleby AmelieSchreiber317updated 3 years ago
Python

This model may be overfit to some extent (see below). Try running this notebook on the datasets linked to in the notebook. See if you can figure out why the metrics differ so much on the datasets. Is it due to something like sequence similarity in the train/test split?

Sourced from

  • HuggingFace — AmelieSchreiber/esm2_t12_35M_lora_binding_sites_v2_cp3

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This model was finetuned on concatenated pairs of interacting proteins in much the same way as PepMLM. It is meant to generate interaction partners for proteins using the masked language modeling capabilities of ESM-2. The model is not well tested, so use with caution.

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This set of model weights was released with the GitHub-compatible esm package format. The models here are kept for backwards compatibility, but we recommend you use the HuggingFace-compatible model weights at biohub/ESMC-6B (or biohub/ESMC-300M / biohub/ESMC-600M) instead.

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This set of model weights was released with the GitHub-compatible esm package format. The models here are kept for backwards compatibility, but we recommend you use the HuggingFace-compatible model weights at biohub/ESMC-6B (or biohub/ESMC-300M / biohub/ESMC-600M) instead.

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