pandallm
Chinese NLP
An open-source project developing and deploying large language models for natural language processing tasks in Chinese.
Panda项目是于2023年5月启动的开源海外中文大语言模型项目,致力于大模型时代探索整个技术栈,旨在推动中文自然语言处理领域的创新和合作。
1k stars
38 watching
90 forks
Language: Python
last commit: almost 3 years agoRelated projects:
| Repository | Description | Stars |
|---|---|---|
| This project provides pre-trained models and tools for natural language understanding (NLU) and generation (NLG) tasks in Chinese. | 439 | |
| Develops and deploys a large language model for Chinese traditional medicine applications | 316 | |
| Provides pre-trained models for Chinese natural language processing tasks using the XLNet architecture | 1,652 | |
| Develops and releases large language models for financial applications with improved performance and features | 1,089 | |
| Develops large language models for text understanding and generation tasks. | 85 | |
| A large language model pre-trained on Chinese and English data, suitable for natural language processing tasks. | 43 | |
| A pre-trained Chinese language model with a modest parameter count, designed to be accessible and useful for researchers with limited computing resources. | 18 | |
| A repository of pre-trained language models for natural language processing tasks in Chinese | 977 | |
| An open bilingual LLM developed using the LingoWhale model, trained on a large dataset of high-quality middle English text, and fine-tuned for specific tasks such as conversation generation. | 134 | |
| This repository contains source files and training scripts for language models. | 12 | |
| Korea University Large Language Model developed by researchers at Korea University and HIAI Research Institute. | 576 | |
| A collection of information about various large language models used in natural language processing | 272 | |
| A large language model designed for research and application in natural language processing tasks. | 887 | |
| A polyglot large language model designed to address limitations in current LLM research and provide better multilingual instruction-following capability. | 77 |