FremyCompany/BioLORD-2023-M

# FremyCompany/BioLORD-2023 This model was trained using BioLORD, a new pre-training strategy for producing meaningful representations for clinical sentences and biomedical concepts.

ProtSent-V2 35M plus one more contrastive pass on a fresh draw of the corpus, with a DMS/ProteinGym CoSENT target and a Global Orthogonal Regularization term added.

ChemFIE-BED is a sentence-transformers based on gbyuvd/chemselfies-base-bertmlm fine-tuned on around (for now) 2 million pairs of valid molecules' SELFIES (Krenn et al. 2020) taken from COCONUTDB (Sorokina et al. 2021) and ChemBL34 (Zdrazil et al. 2023).

A Vision Transformer (ViT) image classification model. \ Trained by Owkin on 40 million pan-cancer histology tiles from TCGA-COAD.

TinyDNABERT is a specialized deep learning model designed for understanding the language of DNA and performing DNA sequence classification tasks. This model is a compact and efficient version of the DNABERT model, optimized to reduce memory usage while maintaining high performance.

This model aims to be a base template for new models. It has been generated using this raw template.