Models (5)
Surface-EMG wristband foundation models that decode hand gestures, handwriting, and wrist movement from thousands of users, generalizing cross-user without per-person calibration.
A large language model trained on 48 million scientific papers and knowledge bases to store, combine, and reason about scientific knowledge.
Meta AI's family of protein language models scaled to 15B parameters, paired with ESMFold for fast, alignment-free atomic-level structure prediction.
Protein language model for zero-shot prediction of mutation effects, achieving state-of-the-art accuracy on deep mutational scanning benchmarks without MSA generation.
Transformer protein language model trained on 250 million protein sequences that learns structural and functional representations without supervision.