MarkSchmidty/ChatGLM-6B-Int4-Web-Demo

22

stars

14

commits

Jupyter Notebook

primary language

Mar 20, 2023

updated

Browse cluster: ChatGLM Language Model Variants

README

ChatGLM-6B-Int4-Web-Demo

Launch In Colab <-- press here to launch the web demo

About ChatGLM

ChatGLM-6B is an open bilingual language model based on General Language Model (GLM) framework, with 6.2 billion parameters. With the quantization technique, users can deploy locally on consumer-grade graphics cards (only 6GB of GPU memory is required at the INT4 quantization level).

ChatGLM-6B uses technology similar to ChatGPT, optimized for Chinese QA and dialogue. The model is trained for about 1T tokens of Chinese and English corpus, supplemented by supervised fine-tuning, feedback bootstrap, and reinforcement learning wit human feedback. With only about 6.2 billion parameters, the model is able to generate answers that are in line with human preference.

Contributors

MarkSchmidty

14 commits

MarkSchmidty/ChatGLM-6B-Int4-Web-Demo

22

stars

14

commits

Jupyter Notebook

primary language

Mar 20, 2023

updated

Browse cluster: ChatGLM Language Model Variants

README

ChatGLM-6B-Int4-Web-Demo

Launch In Colab <-- press here to launch the web demo

About ChatGLM

ChatGLM-6B is an open bilingual language model based on General Language Model (GLM) framework, with 6.2 billion parameters. With the quantization technique, users can deploy locally on consumer-grade graphics cards (only 6GB of GPU memory is required at the INT4 quantization level).

ChatGLM-6B uses technology similar to ChatGPT, optimized for Chinese QA and dialogue. The model is trained for about 1T tokens of Chinese and English corpus, supplemented by supervised fine-tuning, feedback bootstrap, and reinforcement learning wit human feedback. With only about 6.2 billion parameters, the model is able to generate answers that are in line with human preference.

Contributors

MarkSchmidty

14 commits

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