ESM 2 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 fine tune ESM 2 models on your tasks of interest. Several ESM 2 checkpoints are available in the Hub with varying sizes. Larger sizes generally have somewhat better accuracy, but require much more memory and time to train: Checkpoint name Num layers Num parameters esm2 t48 15B UR50D 48 15B esm2 t36 3B UR50D 36 3B esm2 t33 650M UR50D 33 650M esm2 t30 150M UR50D 30 150M esm2 t12 35M UR50D 12 35M esm2 t6 8M UR50D 6 8M
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