Alibaba releases 72B LLM with 32k context length

Nov 30, 2023 ·

This article focuses on the Qwen-72B language model created by HuggingFace. The model is based on an open-source Transformer-XL architecture, which improves upon the performance of existing models. It was trained using a massive amount of text data from Wikipedia and Common Crawl.

Qwen-72B is designed to provide a better understanding of language structure and semantics. Its main features include tokenizing words into subwords, allowing the model to learn from a wide array of words; better predictions of rare words; increased ability to generalize to unseen data; and better contextual understanding. This model also has improved accuracy for long-distance dependencies and memory requirements.

The model can be used for various tasks, such as summarizing, question answering, translation, and text generation. It is also used to improve existing models by fine-tuning them with additional data. In addition, the model can be used in applications such as natural language processing, sentiment analysis, and text classification.

Overall, Qwen-72B is a powerful language model that provides a better understanding of language structure and semantics. Its features make it suitable for many different tasks, from summarizing to question answering. Furthermore, its improved accuracy and low memory requirements make it a valuable asset for applications involving natural language processing.