protein-ml/esm2-t6-8m-ur50d
Overview
ESM-2 is a state-of-the-art protein model trained on a masked language modelling objective. It is suitable for fine-tuning on a wide range of tasks that take protein sequences as input. For detailed information on the model architecture and training data, please refer to the accompanying paper. You may also be interested in some demo notebooks (PyTorch, TensorFlow) which demonstrate how to…
Test this model
baseline-cputhis button is freeAPI: 20 credits per 1,000 residues, minimum 1A CPU baseline answers here, not the catalogued weights — this deployment has no inference cluster. The answers are real and deterministic, and they are not this model's.
Pre-filled with this endpoint's example. Replace it with your own.
Pricing this input…
# Create a token at /settings/tokens with the infer:run scope.
export ATLAS_TOKEN=atlp_…
# What it costs, before spending anything. Free and unmetered, and it runs
# the same count the charge runs -- so {"units": …} is what you will pay for.
curl -sS https://demoatlas.online/protein-ml/esm2-t6-8m-ur50d/infer/quote \
-H "Authorization: Bearer $ATLAS_TOKEN" \
-H "Content-Type: application/json" \
-d '{"input":"MKTAYIAKQRQISFVKSHFSRQLEERLGLIEVQAPILSRVGDGTQDNLSGAEK"}'
# -> {"billingUnit":"residue","units":…,"credits":…}
curl -sS https://demoatlas.online/protein-ml/esm2-t6-8m-ur50d/infer \
-H "Authorization: Bearer $ATLAS_TOKEN" \
-H "Content-Type: application/json" \
-d '{"input":"MKTAYIAKQRQISFVKSHFSRQLEERLGLIEVQAPILSRVGDGTQDNLSGAEK"}'
# Batch: send {"inputs": ["…", "…"]} instead, up to 16 per call.
# Both doors take the same body, so one quote covers the batch you send.The API door charges by the unit consumed — this endpoint counts residues — and takes a batch of up to 16 inputs; this page's button is free and takes one. The /quote call above prices any body without running it, for nothing. Create a token with the infer:run scope, then read the inference docs for the response shapes and the error codes.
Training data
- DATASETprotein-ml/uniref50