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arXiv Machine Learning By Weimin Wu, Xuefeng Song, Yibo Wen, Qinjie Lin, Zhihan Zhou, Jerry Yao-Chieh Hu, Zhong Wang, Han Liu

Genome-Factory: A Library for Tuning, Deploying, and Interpreting Genomic Foundation Models

Read the original on arXiv Machine Learning →

Genome-Factory is the first integrated Python library designed to streamline the entire workflow of genomic foundation model development, covering data collection, model tuning, inference, benchmarking, and interpretability. It provides automated pipelines for downloading and preprocessing genomic sequences, supports both full and parameter‑efficient fine‑tuning for diverse models, and offers tools for embedding extraction, DNA sequence generation, and flexible benchmarking. Additionally, the library includes an open‑source biological interpreter based on a sparse auto‑encoder, validated across compatibility, performance, and biological interpretation dimensions.

Machine-generated by The Flow from the publisher's headline and feed description — not written or checked by a human. The full article lives at arXiv Machine Learning.

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