GENTEL-Lab/EVA

General-purpose RNA language model with 650M parameters pretrained on 36M non-coding RNA sequences, achieving strong generalization on structure prediction tasks including secondary structure prediction, splice-site prediction, mean ribosome loading, and ncRNA classification (lbcb-sci, 165+ stars, Apache-2.0)

# DrugGen 2: A disease-aware language model for enhancing drug discovery DrugGen-2 is a disease‑aware language model specialized for generating drug-like SMILES structures based on both disease pathways and protein sequence.

Chemma-2B is a continually pretrained gemma-2b model for organic molecules. It is pretrained on 40B tokens covering 110M+ molecules from PubChem as well as their chemical properties (molecular weight, synthetic accessibility score, drug-likeness etc.) and similarities (Tanimoto distance between…

Many full-length RNAs, particularly mRNAs, exceed the ~1K context lengths used to pretrain representative dense RNA encoders, forcing long transcripts to be truncated and preventing their 5′ UTR, CDS, and 3′ UTR from being modeled jointly at single-nucleotide resolution.

# Model Card for Model ID More code details can be found at Github: https://github.com/Incredible88/BioMistral-Clinical-7B ## How to use