natural-language-processing

🤗 Transformers: the model-definition framework for state-of-the-art machine learning models in text, vision, audio, and multimodal models, for both inference and training.

Implement a ChatGPT-like LLM in PyTorch from scratch, step by step

《动手学深度学习》：面向中文读者、能运行、可讨论。中英文版被70多个国家的500多所大学用于教学。

Learn how to develop, deploy and iterate on production-grade ML applications.

TensorFlow code and pre-trained models for BERT

中文分词 词性标注 命名实体识别 依存句法分析 成分句法分析 语义依存分析 语义角色标注 指代消解 风格转换 语义相似度 新词发现 关键词短语提取 自动摘要 文本分类聚类 拼音简繁转换 自然语言处理

💫 Industrial-strength Natural Language Processing (NLP) in Python

📚 Papers & tech blogs by companies sharing their work on data science & machine learning in production.

Interactive deep learning book with multi-framework code, math, and discussions. Adopted at 500 universities from 70 countries including Stanford, MIT, Harvard, and Cambridge.

The #1 AI Harness for Building Resumes, PDFs, Cover Letters & more, locally with 100+ LLMs support.

✅（已完结）超级全面的 深度学习 笔记【土堆 Pytorch】【李沐 动手学深度学习】【吴恩达 深度学习】【大飞 大模型Agent】

Repository to track the progress in Natural Language Processing (NLP), including the datasets and the current state-of-the-art for the most common NLP tasks.

🤗 The largest hub of ready-to-use datasets for AI models with fast, easy-to-use and efficient data manipulation tools

The official repo of Qwen (通义千问) chat & pretrained large language model proposed by Alibaba Cloud.

⚡ Automatically decrypt encryptions without knowing the key or cipher, decode encodings, and crack hashes ⚡

💬 Open source machine learning framework to automate text- and voice-based conversations: NLU, dialogue management, connect to Slack, Facebook, and more - Create chatbots and voice assistants

本项目将《动手学深度学习》(Dive into Deep Learning)原书中的MXNet实现改为PyTorch实现。

:book: A curated list of resources dedicated to Natural Language Processing (NLP)

Private AI platform for agents, assistants and enterprise search. Built-in Agent Builder, Deep research, Document analysis, Multi-model support, and API connectivity for agents.

🐫 CAMEL: The first and the best multi-agent framework. Finding the Scaling Law of Agents. https://www.camel-ai.org

📺 Discover the latest machine learning / AI courses on YouTube.

🎨 ML Visuals contains figures and templates which you can reuse and customize to improve your scientific writing.

A comprehensive list of pytorch related content on github,such as different models,implementations,helper libraries,tutorials etc.

Topic Modelling for Humans

Oxford Deep NLP 2017 course

Convert documents to structured data effortlessly. Unstructured is open-source ETL solution for transforming complex documents into clean, structured formats for language models. Visit our website to learn more about our enterprise grade Platform product for production grade workflows, partitioning, enrichments, chunking and embedding.

Style and Grammar Checker for 25+ Languages

Natural Language Processing Tutorial for Deep Learning Researchers

NLTK Source

A very simple framework for state-of-the-art Natural Language Processing (NLP)

Drench yourself in Deep Learning, Reinforcement Learning, Machine Learning, Computer Vision, and NLP by learning from these exciting lectures!!

An open-source, tool-augmented conversational language model from Fudan University

The official GitHub page for the survey paper "A Survey of Large Language Models".

Unsupervised text tokenizer for Neural Network-based text generation.

An open-source NLP research library, built on PyTorch.

Low-code framework for building custom LLMs, neural networks, and other AI models

💥 Fast State-of-the-Art Tokenizers optimized for Research and Production

OpenVINO™ is an open source toolkit for optimizing and deploying AI inference

Open source annotation tool for machine learning practitioners.

Fast and Accurate ML in 3 Lines of Code

This repository contains code examples for the Stanford's course: TensorFlow for Deep Learning Research.

A curated list of practical guide resources of LLMs (LLMs Tree, Examples, Papers)

CoreNLP: A Java suite of core NLP tools for tokenization, sentence segmentation, NER, parsing, coreference, sentiment analysis, etc.