Large-scale Self-supervised Pre-training Across Tasks, Languages, and Modalities
- nlp
- pre-trained-model
- unilm
- minilm
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Large-scale Self-supervised Pre-training Across Tasks, Languages, and Modalities
Unsupervised text tokenizer for Neural Network-based text generation.
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.
An NLP library for building bots, with entity extraction, sentiment analysis, automatic language identify, and so more
Go efficient fast multilingual NLP and text segmentation; support English, Chinese, Japanese and others.
Neural question generation using transformers
🚀 Catalyst is a C# Natural Language Processing library built for speed. Inspired by spaCy's design, it brings pre-trained models, out-of-the box support for training word and document embeddings, and flexible entity recognition models.
RNNLG is an open source benchmark toolkit for Natural Language Generation (NLG) in spoken dialogue system application domains. It is released by Tsung-Hsien (Shawn) Wen from Cambridge Dialogue Systems Group under Apache License 2.0.
Implementation of various topic models
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Modular, fast NLP framework, compatible with Pytorch and spaCy, offering tailored support for French clinical notes.
Rule based Answer Type classification system in Node.js
An NLP library for Uralic languages such as Finnish, Skolt Sami, Moksha and so on. Also supporting some non-Uralic languages such as Spanish, French, Arabic, Swedish, Norwegian, Russian and English. LLMs, FSTs and More!
A Go package for n-gram based text categorization, with support for utf-8 and raw text
A natural language date and time parser for Common Lisp
A flexible and general-purpose ngrams library written in Ruby. Raingrams supports ngram sizes greater than 1, text/non-text grams, multiple parsing styles and open/closed vocabulary models.
Tagify produces a set of tags from a given source. Source can be either an HTML page, a Markdown document or a plain text. Supports English, Russian, Chinese, Hindi, Spanish, Arabic, Japanese, German, Hebrew, French and Korean languages.
Ruby gem to calculate statistics from text to determine readability, complexity and grade level of a particular corpus.
A tokenizer based on the dictionary and Bigram language models for Go. (Now only support chinese segmentation)
Investigating multilingual language models (BERT) by using them for NER in German and English