Models
An Amharic-language variant of Gemma-3-27B-MeditronFO, from EPFL's LiGHT laboratory and the MeditronFO pipeline.
This is the official pre-trained model introduced in DNABERT-2: Efficient Foundation Model and Benchmark For Multi-Species
esm3-sm-open-v1 is trained on 2.78 billion natural proteins.
An encoder-only, half-precision version of the ProtT5-XL-UniRef50 model.
Pretrained model on protein sequences using a masked language modeling (MLM) objective.
An Evolutionary-scale Model (ESM) for protein function prediction from amino acid sequences using the Gene Ontology (GO).
Model Card for ChemBERTa-10M-MTR Model Details Model Description More information needed - Developed by: DeepChem - Shared by [Optional]:
Model artifact mirrored from the HuggingFace Hub.
An Evolutionary-scale Model (ESM) for protein function prediction from amino acid sequences using the Gene Ontology (GO).
ESM Protein Localization Model Model description The ESM Protein Localization Model is a deep learning model trained on protein sequences to predict their…
An Evolutionary-scale Model (ESM) for protein function prediction from amino acid sequences using the Gene Ontology (GO).
The Clinical Assertion and Negation Classification BERT is introduced in the paper Assertion Detection in Clinical Notes: Medical Language Models to the…
This model card describes the ClinicalBERT model, which was trained on a large multicenter dataset with a large corpus of 1.2B words of diverse diseases we…
A Named Entity Recognition model for clinical entities (problem, treatment,
ChemBERTa: Training a BERT-like transformer model for masked language modelling of chemical SMILES
fill-mask artifact mirrored from the HuggingFace Hub.
Pretrained model on protein sequences using a masked language modeling (MLM) objective.
fill-mask artifact mirrored from the HuggingFace Hub.
This is the pretrained model presented in SciBERT: A Pretrained Language Model for Scientific Text, which is a BERT model trained on scientific