Natural Language Processing
Showing 20 of 92 projects
A Java library implementing various string similarity and distance algorithms like Levenshtein, Jaro-Winkler, and n-gram methods.
A high-performance Golang port of the Jieba Chinese text segmentation library.
A curated collection of hands-on data science project ideas and resources for learning machine learning and AI concepts.
A friendly English-like interface for your command line that translates natural language phrases into executable commands.
A JAX/Flax-based framework for easy and scalable pre-training, fine-tuning, evaluation, and serving of large language models.
A natural language processor powered by plugins that transforms and analyzes text using syntax trees.
A modular toolkit for machine learning, natural language processing, and text generation with TensorFlow and PyTorch versions.
A Python NLP library built on spaCy for text preprocessing, feature extraction, and analysis tasks.
A curated collection of R tutorials, packages, and resources for Data Science, NLP, and Machine Learning.
A spaCy pipeline and models specifically designed for processing scientific and biomedical documents.
A self-contained machine learning and natural language processing library written in pure Go with a dynamic computational graph.
A Python package for fine-tuning and generating text with GPT-2 and GPT Neo models using PyTorch and Hugging Face Transformers.
A library for creating TensorFlow models that handle structured data with dynamic computation graphs using dynamic batching.
A Go library and CLI tool for converting Chinese characters to Hanyu Pinyin with tone support.
Implementations of memory-augmented neural networks for language modeling, dialogue systems, and question answering tasks.
A collection of models, callbacks, and datasets to extend PyTorch Lightning for applied AI/ML research and production.
An easy-to-use, state-of-the-art named-entity recognition (NER) tool based on neural networks.
A BERT language model pre-trained on a large corpus of scientific papers for natural language processing tasks in scientific domains.
A deep learning model for machine comprehension that uses bi-directional attention flow to answer questions about text passages.
A curated list of resources for Document Understanding (DU), covering research, datasets, tools, and applications in Intelligent Document Processing.
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