Lists (5)
Stars
A feature-rich command-line audio/video downloader
Magnificent app which corrects your previous console command.
A curated list of awesome Machine Learning frameworks, libraries and software.
为GPT/GLM等LLM大语言模型提供实用化交互接口，特别优化论文阅读/润色/写作体验，模块化设计，支持自定义快捷按钮&函数插件，支持Python和C++等项目剖析&自译解功能，PDF/LaTex论文翻译&总结功能，支持并行问询多种LLM模型，支持chatglm3等本地模型。接入通义千问, deepseekcoder, 讯飞星火, 文心一言, llama2, rwkv, claude2, m…
The official gpt4free repository | various collection of powerful language models | o4, o3 and deepseek r1, gpt-4.1, gemini 2.5
A high-throughput and memory-efficient inference and serving engine for LLMs
LlamaIndex is the leading framework for building LLM-powered agents over your data.
Making large AI models cheaper, faster and more accessible
An open platform for training, serving, and evaluating large language models. Release repo for Vicuna and Chatbot Arena.
💫 Industrial-strength Natural Language Processing (NLP) in Python
DSPy: The framework for programming—not prompting—language models
Pretrain, finetune ANY AI model of ANY size on 1 or 10,000+ GPUs with zero code changes.
SearXNG is a free internet metasearch engine which aggregates results from various search services and databases. Users are neither tracked nor profiled.
A set of examples around pytorch in Vision, Text, Reinforcement Learning, etc.
Large-scale Self-supervised Pre-training Across Tasks, Languages, and Modalities
Best Practices on Recommendation Systems
🆓免费的 ChatGPT 镜像网站列表，持续更新。List of free ChatGPT mirror sites, continuously updated.
Use ChatGPT to summarize the arXiv papers. 全流程加速科研，利用chatgpt进行论文全文总结+专业翻译+润色+审稿+审稿回复
中文LLaMA&Alpaca大语言模型+本地CPU/GPU训练部署 (Chinese LLaMA & Alpaca LLMs)
Evals is a framework for evaluating LLMs and LLM systems, and an open-source registry of benchmarks.
A Python library for extracting structured information from unstructured text using LLMs with precise source grounding and interactive visualization.
Machine Learning Engineering Open Book
ChatGLM2-6B: An Open Bilingual Chat LLM | 开源双语对话语言模型
Python package built to ease deep learning on graph, on top of existing DL frameworks.