🤗 Transformers: State-of-the-art Machine Learning for Pytorch, TensorFlow, and JAX.
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Updated
Dec 13, 2023 - Python
🤗 Transformers: State-of-the-art Machine Learning for Pytorch, TensorFlow, and JAX.
Natural Language Processing Tutorial for Deep Learning Researchers
🏄 Scalable embedding, reasoning, ranking for images and sentences with CLIP
🔍 LLM 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.
👑 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, ℹ️ Information Extraction, 📄 Document Intelligence, 💌 Sentiment Analysis etc.
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
💥 Fast State-of-the-Art Tokenizers optimized for Research and Production
This repository contains demos I made with the Transformers library by HuggingFace.
Official implementations for various pre-training models of ERNIE-family, covering topics of Language Understanding & Generation, Multimodal Understanding & Generation, and beyond.
BertViz: Visualize Attention in NLP Models (BERT, GPT2, BART, etc.)
Google AI 2018 BERT pytorch implementation
Leveraging BERT and c-TF-IDF to create easily interpretable topics.
Transformer related optimization, including BERT, GPT
Tensorflow solution of NER task Using BiLSTM-CRF model with Google BERT Fine-tuning And private Server services
Tutorials on getting started with PyTorch and TorchText for sentiment analysis.
A LITE BERT FOR SELF-SUPERVISED LEARNING OF LANGUAGE REPRESENTATIONS, 海量中文预训练ALBERT模型
Must-read papers on prompt-based tuning for pre-trained language models.
中文语言理解测评基准 Chinese Language Understanding Evaluation Benchmark: datasets, baselines, pre-trained models, corpus and leaderboard
该仓库主要记录 NLP 算法工程师相关的顶会论文研读笔记
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