FAQ-Semantic-Retrieval

? Transformers: State-of-the-art Machine Learning for Pytorch, TensorFlow, and JAX.

AI orchestration framework to build customizable, production-ready LLM applications. Connect components (models, vector DBs, file converters) to pipelines or agents that can interact with your data. With advanced retrieval methods, it's best suited for building RAG, question answering, semantic search or conversational agent chatbots.

《李宏毅深度学习教程》（李宏毅老师推荐?，苹果书?），PDF下载地址：https://github.com/datawhalechina/leedl-tutorial/releases

Natural Language Processing Tutorial for Deep Learning Researchers

? Easy-to-use and powerful NLP and LLM library with ? Awesome model zoo, supporting wide-range of NLP tasks from research to industrial applications, including ?Text Classification, ? Neural Search, ? Question Answering, ?? Information Extraction, ? Document Intelligence, ? Sentiment Analysis etc.

? Scalable embedding, reasoning, ranking for images and sentences with CLIP

This repository contains demos I made with the Transformers library by HuggingFace.

Pre-Training with Whole Word Masking for Chinese BERT（中文BERT-wwm系列模型）

大规模中文自然语言处理语料 Large Scale Chinese Corpus for NLP

BertViz: Visualize Attention in NLP Models (BERT, GPT2, BART, etc.)