| Property | Value |
|---|---|
| Parameter Count | 3 Billion |
| Number of Layers | 36 |
| License | MIT |
| Author |
What is esm2_t36_3B_UR50D?
ESM2_t36_3B_UR50D is a state-of-the-art protein language model developed by Facebook, featuring 3 billion parameters across 36 layers. It represents one of the medium-large variants in the ESM-2 model family, designed specifically for protein sequence analysis through masked language modeling.
Implementation Details
The model is implemented using PyTorch and supports both PyTorch and TensorFlow frameworks. It utilizes a transformer-based architecture and has been trained on protein sequences using a masked language modeling objective. With over 1.6 million downloads, it has proven to be a popular choice in the scientific community.
- 36-layer transformer architecture
- 3 billion parameters for deep protein sequence understanding
- Supports masked language modeling tasks
- Available through Hugging Face's model hub
Core Capabilities
- Protein sequence analysis and prediction
- Masked language modeling for protein sequences
- Fine-tuning capabilities for specific protein-related tasks
- Protein structure and function prediction support
Frequently Asked Questions
Q: What makes this model unique?
This model offers a balanced trade-off between computational requirements and performance, with its 3B parameters providing excellent protein sequence analysis capabilities while being more manageable than the 15B parameter variant.
Q: What are the recommended use cases?
The model is ideal for protein sequence analysis, structure prediction, and protein engineering applications. It can be fine-tuned for specific tasks and is particularly well-suited for research requiring deep understanding of protein sequences.