Pinned Repositories
BI-LSTM-sentiment-classify
ChuanhuChatGPT
GUI for ChatGPT API and many LLMs. Supports agents, file-based QA, GPT finetuning and query with web search. All with a neat UI.
CNKI-selenium-crawler
知网论文数据爬虫
enhance_llm
LLM&ebedding
from_scratch_LLM
llm and vlm core code
Langchain-Chatchat
Langchain-Chatchat（原Langchain-ChatGLM）基于 Langchain 与 ChatGLM 等语言模型的本地知识库问答 | Langchain-Chatchat (formerly langchain-ChatGLM), local knowledge based LLM (like ChatGLM) QA app with langchain
Llama2-Chinese
Llama中文社区，最好的中文Llama大模型，完全开源可商用
MediaCrawler
小红书笔记 | 评论爬虫、抖音视频 | 评论爬虫、快手视频 | 评论爬虫、B 站视频 ｜ 评论爬虫、微博帖子 ｜ 评论爬虫
NotionNext
使用 NextJS + Notion API 实现的，支持多种部署方案的静态博客，无需服务器、零门槛搭建网站，为Notion和所有创作者设计。 (A static blog built with NextJS and Notion API, supporting multiple deployment options. No server required, zero threshold to set up a website. Designed for Notion and all creators.)
weibo-public-opinion-analysis
基于微博数据的舆情分析项目，包括微博爬虫、LDA主题分析和情感分析。
stay-leave's Repositories
stay-leave/weibo-public-opinion-analysis
基于微博数据的舆情分析项目，包括微博爬虫、LDA主题分析和情感分析。
stay-leave/enhance_llm
LLM&ebedding
stay-leave/CNKI-selenium-crawler
知网论文数据爬虫
stay-leave/BI-LSTM-sentiment-classify
stay-leave/MediaCrawler
小红书笔记 | 评论爬虫、抖音视频 | 评论爬虫、快手视频 | 评论爬虫、B 站视频 ｜ 评论爬虫、微博帖子 ｜ 评论爬虫
stay-leave/ChuanhuChatGPT
GUI for ChatGPT API and many LLMs. Supports agents, file-based QA, GPT finetuning and query with web search. All with a neat UI.
stay-leave/from_scratch_LLM
llm and vlm core code
stay-leave/Langchain-Chatchat
Langchain-Chatchat（原Langchain-ChatGLM）基于 Langchain 与 ChatGLM 等语言模型的本地知识库问答 | Langchain-Chatchat (formerly langchain-ChatGLM), local knowledge based LLM (like ChatGLM) QA app with langchain
stay-leave/Llama2-Chinese
Llama中文社区，最好的中文Llama大模型，完全开源可商用
stay-leave/NotionNext
使用 NextJS + Notion API 实现的，支持多种部署方案的静态博客，无需服务器、零门槛搭建网站，为Notion和所有创作者设计。 (A static blog built with NextJS and Notion API, supporting multiple deployment options. No server required, zero threshold to set up a website. Designed for Notion and all creators.)
stay-leave/RAG-Survey
Collecting awesome papers of RAG for AIGC. We propose a taxonomy of RAG foundations, enhancements, and applications in paper "Retrieval-Augmented Generation for AI-Generated Content: A Survey".
stay-leave/ShiArthur03