Hugging Face Transformers
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Find sources: "Hugging Face Transformers" – news · newspapers · books · scholar · JSTOR Reviewer tools: guideline project (talk • log) The article may be deleted if this message remains in place for five days, i.e., after 12:23, 30 October 2026 (UTC). |
| Hugging Face Transformers | |
|---|---|
| Developer | Hugging Face |
| Release | November 17, 2018 |
| Stable release | |
| Written in | Python |
| Type | Deep learning library |
| License | Apache License 2.0 |
| Website | huggingface |
| Repository | |
Hugging Face Transformers is an open-source deep learning library developed by Hugging Face. It provides implementations of pretrained transformer and other neural network models for training and inference, including models for text, images, audio, video, and multimodal learning.[2][3]
History
[edit]Transformers was first released in November 2018 as pytorch-pretrained-bert, a PyTorch implementation of BERT.[4] It was later renamed pytorch-transformers as support expanded to additional transformer models, before becoming Transformers.[5]
By September 2019, its PyTorch version had been pip installed more than 500,000 times that year and was being used by more than 1,000 companies, according to VentureBeat.[6] Version 5, released in 2025, made PyTorch the library's sole machine learning backend, ending direct support for TensorFlow and JAX.[7]
Features
[edit]Transformers provides standardized model definitions and tools for downloading, running, and training pretrained machine learning models.[8] It is used for tasks including text generation, machine translation, text classification, question answering, image classification, object detection, speech synthesis, and speech recognition. Models can be downloaded from and shared through the Hugging Face Hub.[9]
See also
[edit]References
[edit]- ↑ "Release 5.20.2". 19 October 2026. Retrieved 20 October 2026.
- ↑ Wolf, Thomas; Debut, Lysandre; Sanh, Victor; Chaumond, Julien; Delangue, Clement (2020). "Transformers: State-of-the-Art Natural Language Processing". Proceedings of the 2020 Conference on Empirical Methods in Natural Language Processing: System Demonstrations. Association for Computational Linguistics. pp. 38–45. doi:10.18653/v1/2020.emnlp-demos.6.
- ↑ "Hugging Face launches popular Transformers NLP library for TensorFlow". VentureBeat. September 26, 2019. Retrieved September 3, 2026.
- ↑ "pytorch-pretrained-bert". Python Package Index. Retrieved September 3, 2026.
- ↑ "Migrating from previous packages". Hugging Face. Retrieved September 3, 2026.
- ↑ "Hugging Face launches popular Transformers NLP library for TensorFlow". VentureBeat. September 26, 2019. Retrieved September 3, 2026.
- ↑ "Transformers v5: Simple model definitions powering the AI ecosystem". Hugging Face. December 1, 2025. Retrieved September 3, 2026.
- ↑ "Transformers". GitHub. Hugging Face. Retrieved September 3, 2026.
- ↑ "Using Transformers at Hugging Face". Hugging Face. Retrieved September 3, 2026.