ESM-2 Protein Language Model Explained – Architecture & Training

Описание: In this video, we introduce the ESM-2 protein language model, one of the most widely used transformer-based models for sequence-based protein prediction tasks.
We explain the model architecture, Rotary Positional Embeddings (RoPE), and the self-supervised masked language modeling objective that makes ESM-2 so powerful for downstream protein property prediction.


📚References
ESM-2 paper (Lin et al., Science)
“Evolutionary-scale prediction of atomic-level protein structure with a language model”
DOI: https://doi.org/10.1126/science.ade2574

ESM-2 Python code walkthrough & fine-tuning (Part 2 video)
   • Using ESM-2 in Python: Protein Embeddings ...  

Jupyter notebook for ESM-2 fine-tuning & analysis
https://github.com/ProteinVision/ESM2...


🎵Credits
Intro music: “Unbreakable” – Pixabay Music
https://pixabay.com/music/main-title-...


🧬About ProteinVision
We are ProteinVision, and we develop state-of-the-art models for protein prediction tasks.
🌐 Homepage: https://protein.vision
📧 Contact: [email protected]
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