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.
pip install -U -q keras-hub
pip install -U -q keras
Jax, TensorFlow, and Torch come preinstalled in Kaggle Notebooks. For instructions on installing them in another environment see the Keras Getting Started page.
Presets
The following model checkpoints are provided by the Keras team. Weights have been ported from: https://huggingface.co. Full code examples for each are available below.
Preset name
Parameters
Description
esm2_t6_8M
8M
6 transformer layers version of the ESM-2 protein language model, trained on the UniRef50 clustered protein sequence dataset.
esm2_t12_35M
35M
12 transformer layers version of the ESM-2 protein language model, trained on the UniRef50 clustered protein sequence dataset.
esm2_t30_150M
150M
30 transformer layers version of the ESM-2 protein language model, trained on the UniRef50 clustered protein sequence dataset.
esm2_t33_650M
650M
33 transformer layers version of the ESM-2 protein language model, trained on the UniRef50 clustered protein sequence dataset.
