esmlisted

# ESM: Evolutionary Scale Modeling ## Overview ESM provides protein language models for understanding, generating, and designing proteins. Use this skill for current EvolutionaryScale/Biohub workflows: ESM3 for generative design, ESMC for representation learning and embeddings, hosted Forge/Biohub inference, and ESMFold2 all-atom structure prediction. ## Core Capabilities ### 1. Protein Sequence Generation with ESM3 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:** ```python from esm.models.esm3 import ESM3 from esm.sdk.api import ESM3InferenceClient, ESMProtein, GenerationConfig # Load local open weights after accepting the license on Hugging Face. model: ESM3InferenceClient = ESM3.from_pretrained("esm3-open").to("cuda") # Create protein prompt protein = ESMProtein(sequence="MPRT___KEND") # '_' represents masked positions # Generate completion protein = model.generate(protein, GenerationConfig(track="sequence", num_steps=8)) print(protein.sequence) ``` **For remote/cloud usage via Forge API:** ```python import os import esm from esm.sdk.api import ESMProtein, GenerationConfig # Same interface as local ESM3; token from ESM_API_KEY (see Authentication) model = esm.sdk.client("esm3-medium-2