esm

原文涵盖的主题

• ESM: Evolutionary Scale Modeling
• Overview
• Core Capabilities
• 1. Protein Sequence Generation with ESM3
• 2. Structure Prediction and Inverse Folding
• 3. Protein Embeddings with ESM C
• 4. Function Conditioning and Annotation
• 5. Chain-of-Thought Generation

ESM provides state-of-the-art protein language models for understanding, generating, and designing proteins. This skill enables working with two model families: ESM3 for generative protein design across sequence, structure, and function, and ESM C for efficient protein representation learning and embeddings. Generate novel protein sequences with desired properties using multimodal generative modeling. When to use: Designing proteins with specific functional properties Completing partial protein sequences Generating variants of existing proteins Creating proteins with desired structural characteristics Basic usage: For remote/cloud usage via Forge API: See references/esm3-api.md for detailed ESM3 model specifications, advanced generation configurations, and multimodal prompting examples. Use ESM3's structure track for structure prediction from sequence or inverse folding (sequence design from structure). Structure prediction: Inverse folding (sequence from structure): Generate high-quality embeddings for downstream tasks like function prediction, classification, or similarity analysis. When to use: Extracting protein representations for machine learning Computing sequence similariti

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