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esm

Design, analyze, and embed proteins with ESM3 and ESM C models.

48|6|Updated Mar 9, 2026
Search Tags:#embeddings#inverse-folding#protein-design#structure-prediction#esm3#forge-api
One-click install
npx skills add https://github.com/qinyan-ai/qinyan-academic-skills --skill esm-qinyan-ai
Or copy as Structured Prompt for Agent▼
Please help me install this Agent Skill.
Skill: esm
Source: https://github.com/qinyan-ai/qinyan-academic-skills/tree/main/skills/08-%E8%9B%8B%E7%99%BD%E8%B4%A8%E5%B7%A5%E7%A8%8B%E4%B8%8E%E7%BB%93%E6%9E%84%E7%94%9F%E7%89%A9%E5%AD%A6/esm
Command: npx skills add https://github.com/qinyan-ai/qinyan-academic-skills --skill esm-qinyan-ai

SYSTEM DOCUMENTATION & REQUIREMENTS

💡 This Skill includes references (resource) components.

What problem does it solve?

Enables researchers to design, analyze, and embed proteins using ESM3 multimodal generation and ESM C embeddings in a unified toolkit.

Core Features & Use Cases

  • Multimodal protein design across sequence, structure, and function with ESM3.
  • Efficient protein embeddings and representations with ESM C for downstream ML tasks.
  • Structure prediction, inverse folding, and function conditioning workflows.
  • Cloud-based Forge API support for scalable inference and batch processing.

Quick Start

Install the skill and run a minimal example to generate a short protein sequence with ESM3 locally.

Frequently Asked Questions about esm

High-intent search queries and answers about installing and using this skill.

FAQPage Schema
How do I generate protein embeddings for downstream machine learning tasks?▼

You can compute protein embeddings by running the ESM C models included in this toolkit. It generates numerical representations of protein sequences locally or via the Forge API, providing the vector outputs needed for downstream ML tasks.

Can I perform protein inverse folding and structure prediction in the same workflow?▼

Yes, inverse folding and structure prediction are supported natively within the ESM3 multimodal workflows. You can condition protein sequence generation on structural constraints and predict structures from sequences without switching frameworks.

What is multimodal protein design with ESM3 and how does it condition sequence generation?▼

Multimodal protein design with ESM3 generates novel proteins by conditioning across sequence, structure, and function simultaneously. It allows researchers to specify desired structural or functional traits to guide the automated sequence design process.

Do I need Forge API access to run ESM3 models for protein design?▼

You do not need Forge API access for basic local experimentation, as minimal protein sequence generation can run locally. Forge API is required for scalable cloud inference, accessing large ESM3 models, and executing batch processing workflows.

How do I set up the Python environment to start using ESM for protein analysis?▼

You need a Python environment with the official esm package installed to use this toolkit. Once the package and its dependencies are configured, you can initialize the frontfrontmatter-defined skill entry to enable discovery and run local analysis.

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