Foundation Models
Showing 6 of 6 projects
An automated machine learning library that trains and deploys high-accuracy models for tabular, text, image, and time series data with minimal code.
A collection of transformer-based foundation models for genomics and transcriptomics, enabling tasks like sequence analysis, functional prediction, and conversational DNA exploration.
A long-range genomic foundation model that processes DNA sequences up to 1 million nucleotides at single nucleotide resolution.
A JAX-based framework for training large language models with a focus on legibility, scalability, and reproducibility.
A curated collection of databases, software, and papers for computational biology research.
A multitask generative pre-trained language model for zero-shot cell type annotation, batch integration, and conditional cell generation in single-cell transcriptomics.
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