ESMC Model Details ESMC is a state of the art protein language model that has learned the rules of protein biology from training on billions of protein sequences. ESMC provides representations of proteins enabling novel AI applications from therapeutic protein engineering to unlocking basic insights into protein biology across life. The ESMC 6B model has 6 billion parameters, with 80 layers and 2.37e23 training flops. We additionally release overtrained 300M and 600M parameter variants of ESMC for local inference and finetuning. The ESMFold2 structure prediction models are trained on top of a frozen ESMC 6B language model. ESMFold2 is a state of the art model for protein structure prediction and design that defines a new frontier for speed and accuracy. The ESMC sparse autoencoder, ESMC 6B sae layer60 k64 codebook16384 , is built on the ESMC 6B model and provides human interpretable, agent generated feature descriptions. See the ESMC SAE overview card for the full set of ESMC SAE variants. To run this model with the Biohub Platform API, visit the Biohub Platform. Read more about ESMC in our paper here. Example Usage Install esm from GitHub (a PyPI release is coming soon): By defaul…
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