Updated: Aug 1
Hugging Face's Transformers is a popular open-source library for natural language processing (NLP). It provides a high-level API for accessing and using pre-trained transformer models, which are a type of deep learning model that has been shown to be very effective for a variety of NLP tasks.
Transformers were first introduced in the paper "Attention Is All You Need" by Vaswani et al. (2017). They are based on the attention mechanism, which allows the model to learn long-range dependencies between different parts of the input sequence. This makes them well-suited for tasks such as machine translation, text summarization, and question-answering. Hugging Face's Transformers library provides a unified API for accessing a variety of pre-trained transformer models. These models have been trained on large datasets of text and code, and they can be used to perform various NLP tasks. For example, the library includes models for machine translation, text summarization, question answering, and natural language inference.
The library is easy to use and it is compatible with a variety of programming languages, including Python, Java, and R. It is also well-documented and there is a large community of users and developers who can provide support.
Hugging Face's Transformers is a powerful tool for NLP research and development. It provides a simple and efficient way to access and use pre-trained transformer models, which can save researchers and developers a significant amount of time and effort.
Vaswani, A., Shazeer, N., Parmar, N., Uszkoreit, J., Jones, L., Gomez, A. N., ... & Senior, A. W. (2017). Attention is all you need. In Advances in neural information processing systems (pp. 5865-5874).