Popular GitHub Repositories for Clinical Bert

? 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.

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

vits2 backbone with multilingual-bert

Chinese version of GPT2 training code, using BERT tokenizer.

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

Leveraging BERT and c-TF-IDF to create easily interpretable topics.

Google AI 2018 BERT pytorch implementation

TensorFlow 2.x version's Tutorials and Examples, including CNN, RNN, GAN, Auto-Encoders, FasterRCNN, GPT, BERT examples, etc. TF 2.0版入门实例代码，实战教程。

Transformer related optimization, including BERT, GPT

Awesome Pretrained Chinese NLP Models，高质量中文预训练模型&大模型&多模态模型&大语言模型集合

Tensorflow solution of NER task Using BiLSTM-CRF model with Google BERT Fine-tuning And private Server services

text2vec, text to vector. 文本向量表征工具，把文本转化为向量矩阵，实现了Word2Vec、RankBM25、Sentence-BERT、CoSENT等文本表征、文本相似度计算模型，开箱即用。

Tutorials on getting started with PyTorch and TorchText for sentiment analysis.

Must-read papers on prompt-based tuning for pre-trained language models.