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Esm2 T36 3B UR50D
ESM-2 is a next-generation protein model trained with masked language modeling objectives, suitable for fine-tuning on various downstream tasks with protein sequences as input.
Downloads 3.5M
Release Time : 10/13/2022
Model Overview
ESM-2 is a protein language model trained with masked language modeling objectives, capable of understanding and generating protein sequences, and suitable for tasks such as protein structure prediction and functional annotation.
Model Features
Large-scale pre-training
The model is pre-trained on extensive protein sequence data, possessing robust sequence understanding and generation capabilities.
Multi-scale options
Offers models ranging from 8 million to 15 billion parameters to accommodate different computational resource needs.
Downstream task adaptation
The model design considers the fine-tuning requirements for various protein-related downstream tasks.
Model Capabilities
Protein sequence modeling
Protein masked prediction
Protein structure prediction
Protein functional annotation
Use Cases
Bioinformatics
Protein structure prediction
Utilizes the model's understanding of protein sequences to predict their three-dimensional structures.
Protein functional annotation
Analyzes protein sequences through the model to predict their potential functions.
Drug discovery
Protein design
Uses the model to generate protein sequences with specific functions.
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