ESM-2 650M (Protein Embeddings)
Meta AI 650M-parameter protein language model trained on UniRef50 sequences. Feed it an amino-acid sequence and the per-residue hidden states act as learned protein embeddings, used for structure prediction, variant-effect and function tasks. This 33-layer checkpoint is the common balance of quality and cost in the ESM-2 family.
ESM-2 650M (Protein Embeddings) is embeddings AI model from huggingface, priced at €0.000 per 1M input tokens with a 1.0K tokens context window.
About this model
Pricing
API Integration
Use our OpenAI-compatible API to integrate ESM-2 650M (Protein Embeddings) into your application.
npm install railwailimport railwail from "railwail";
const rw = railwail("YOUR_API_KEY");
const vectors = await rw.run("esm2-650m-protein-embeddings", "Hello world", { type: "embed" });
console.log(vectors[0].length); // embedding dimensions
// Or use the embed() method for full control
const res = await rw.embed("esm2-650m-protein-embeddings", ["Hello", "World"]);
for (const item of res.data) {
console.log(item.embedding.length);
}Frequently asked questions
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