mlsanityData to 14 Oct 2026

HuggingFace's Transformers: State-of-the-art Natural Language Processing

arXiv 1910.03771 ↗First posted 9 Oct 2019cs.CLcited by 2,218

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Cited by 129 in LLM reasoning, but placed by its own abstract, which didn’t fit.

Abstract (arXiv)

Recent progress in natural language processing has been driven by advances in both model architecture and model pretraining. Transformer architectures have facilitated building higher-capacity models and pretraining has made it possible to effectively utilize this capacity for a wide variety of tasks. textitTransformers is an open-source library with the goal of opening up these advances to the wider machine learning community. The library consists of carefully engineered state-of-the art Transformer architectures under a unified API. Backing this library is a curated collection of pretrained models made by and available for the community. textitTransformers is designed to be extensible by researchers, simple for practitioners, and fast and robust in industrial deployments. The library is available at urlhttps://github.com/huggingface/transformers.

Key facts. Cited by 2,218 papers in the map (data through 14 Oct 2026). First posted on arXiv 9 Oct 2019.

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Citing papers per year: 2020: 2; 2021: 284; 2022: 290; 2023: 345; 2024: 564; 2025: 488; 2026: 245.

2,218 papers.

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