ChatGLM: A Lightweight Alternative to OpenAI’s ChatGPT with Enhanced Capabilities

Introduction of ChatGPT by OpenAI gained immense popularity and sparked advancements in the field of natural language conversation agents. Researchers are actively working on enhancing chatbot models to improve their interactions with users. One such alternative to ChatGPT is the ChatGLM model series developed by researchers at Tsinghua University. This series, based on the General Language Model (GLM) framework, offers several bilingual models trained in Chinese and English. The most well-known model in this series is ChatGLM-6B, which has gained popularity with over 2 million downloads worldwide.

ChatGLM-6B is lightweight and can be deployed locally on consumer-grade graphics cards. It has become one of the most influential large-scale open-source models. Tsinghua University researchers released the second-generation version, ChatGLM2-6B, which includes enhancements like performance improvements, support for longer contexts, and more efficient inference. The model has been trained on over 1.4 trillion English and Chinese tokens and outperforms other models of similar size in various datasets. Noteworthy upgrades include support for longer contexts of up to 32K and lower GPU memory usage, resulting in increased inference speed.

Tsinghua University has open-sourced ChatGLM2-6B to encourage developers and researchers worldwide to utilize LLMs for creating innovative applications. However, given the model’s smaller scale, its outputs should be carefully fact-checked for accuracy. The team is already working on the third version of the model, ChatGLM3. To learn more about ChatGLM2-6B, you can visit the Github link provided.

Keywords: AI, ChatGLM, ChatGPT, natural language conversation agents, GLM framework, bilingual models, Chinese, English, lightweight, local deployment, performance improvements, longer contexts, efficient inference, open-source, Tsinghua University, Github

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