🤗 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.
- nlp
- natural-language-processing
- pytorch
- pytorch-transformers
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🤗 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.
A Python library for extracting structured information from unstructured text using LLMs with precise source grounding and interactive visualization.
TranslatedChinese word segmentation, part-of-speech tagging, named entity recognition, dependency parsing, constituency parsing, semantic dependency parsing, semantic role labeling, coreference resolution, style transfer, semantic similarity, new word discovery, keyword and keyphrase extraction, automatic summarization, text classification and clustering, pinyin and Simplified/Traditional Chinese conversion, natural language processing
Non-autoregressive System 1 decision engine. Typed choice, score and yes/no decisions over any text in a single forward pass, in 100+ languages, with a router that picks the right checkpoint per request.
💫 Industrial-strength Natural Language Processing (NLP) in Python
Large-scale Self-supervised Pre-training Across Tasks, Languages, and Modalities
Offline, privacy-first grammar checker. Fast, open-source, Rust-powered
Topic Modelling for Humans
State-of-the-art Machine Learning for the web. Run 🤗 Transformers directly in your browser, with no need for a server!
Style and Grammar Checker for 25+ Languages
Pretrained models for TensorFlow.js
A very simple framework for state-of-the-art Natural Language Processing (NLP)
Easy-to-use and powerful LLM and SLM library with awesome model zoo.
modest natural-language processing
Multi-layer Recurrent Neural Networks (LSTM, GRU, RNN) for character-level language models in Torch
An open-source framework for detecting, redacting, masking, and anonymizing sensitive data (PII) across text, images, and structured data. Supports NLP, pattern matching, and customizable pipelines.
💥 Fast State-of-the-Art Tokenizers optimized for Research and Production
CoreNLP: A Java suite of core NLP tools for tokenization, sentence segmentation, NER, parsing, coreference, sentiment analysis, etc.
Simple, Pythonic, text processing--Sentiment analysis, part-of-speech tagging, noun phrase extraction, translation, and more.
Leveraging BERT and c-TF-IDF to create easily interpretable topics.
all kinds of text classification models and more with deep learning
Stanford NLP Python library for tokenization, sentence segmentation, NER, and parsing of many human languages
An open source library for deep learning end-to-end dialog systems and chatbots.
Officially maintained, supported by PaddlePaddle, including CV, NLP, Speech, Rec, TS, big models and so on.