GENERanno
Collection
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How to use GenerTeam/GENERanno-prokaryote-0.5b-cds-annotator with Transformers:
# Use a pipeline as a high-level helper
from transformers import pipeline
pipe = pipeline("token-classification", model="GenerTeam/GENERanno-prokaryote-0.5b-cds-annotator", trust_remote_code=True, device_map="auto") # Load model directly
from transformers import AutoModelForTokenClassification
model = AutoModelForTokenClassification.from_pretrained("GenerTeam/GENERanno-prokaryote-0.5b-cds-annotator", trust_remote_code=True, dtype="auto", device_map="auto")In this repository, we present GENERanno-cds-annotator, which is meticulously finetuned on GENERanno-prokaryote-0.5b-base for metagenomic annotation tasks. Through comprehensive evaluations, GENERanno-cds-annotator achieves superior accuracy compared to traditional HMM-based methods (e.g., GLIMMER3, GeneMarkS2, Prodigal) and recent LLM-based approaches (e.g., GeneLM), while demonstrating exceptional generalization ability on archaeal genomes.
Python scripts for end-to-end genome annotation is avaliable on GitHub: GenerTeam
@article{li2025generanno,
author = {Li, Qiuyi and Wu, Wei and Zhu, Yiheng and Feng, Fuli and Ye, Jieping and Wang, Zheng},
title = {GENERanno: A Genomic Foundation Model for Metagenomic Annotation},
elocation-id = {2025.06.04.656517},
year = {2025},
doi = {10.1101/2025.06.04.656517},
publisher = {Cold Spring Harbor Laboratory},
URL = {https://www.biorxiv.org/content/early/2025/06/05/2025.06.04.656517},
journal = {bioRxiv}
}
Base model
GenerTeam/GENERanno-prokaryote-0.5b-base