Awesome Data Analysis
Section: Tools · Python NLP library for many human languages, from the Stanford NLP Group.
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Appears in 5 awesome lists
Stanford NLP Python library for 100+ human languages. State-of-the-art neural pipelines for tokenization, NER, parsing, and sentiment analysis with pre-trained models. Apache 2.0 licensed.
Section: Tools · Python NLP library for many human languages, from the Stanford NLP Group.
Section: Libraries · Stanford NLP's Python toolkit for tokenization, POS, lemma, dependency parsing, and NER across 70+ languages.
Section: 11. Specialized Domains · Stanford NLP Python library for 100+ human languages. State-of-the-art neural pipelines for tokenization, NER, parsing, and sentiment analysis with pre-trained models. Apache 2.0 licensed.
Section: Natural Language Processing · Stanford NLP Python library for tokenization, sentence segmentation, NER, and parsing of many human languages
Section: Natural Language Processing · The Stanford NLP Group's official Python library, supporting 60+ languages.
(formerly known as pytorch-transformers and pytorch-pretrained-bert) provides state-of-the-art general-purpose architectures (BERT, GPT-2, RoBERTa, XLM, DistilBert, XLNet, CTRL...) for Natural Language Understanding (NLU) and Natural Language Generation (NLG) with over 32+ pretrained models in…
Open-source AI orchestration framework for building context-engineered, production-ready LLM applications. Design modular pipelines and agent workflows with explicit control over retrieval, routing, memory, and generation. Built for scalable agents, RAG, multimodal applications, semantic search,…
Modern, comprehensive probabilistic programming framework in Python. Bayesian modeling with advanced MCMC sampling, variational inference, and seamless integration with ArviZ for visualization. Apache 2.0 licensed.
A curated list of resources dedicated to Natural Language Processing and text processing for Ruby.
PyTorch version of Stable Baselines, reliable implementations of reinforcement learning algorithms.
Industrial-strength natural language processing with 75+ languages, transformer pipelines, and production-grade NER, parsing, and text classification.
Quantitative finance: multi-agent AI hedge fund trading system featuring native JevLLM integration to execute fast typed decisions without parsing fragility.
FAIR's next-generation research platform for object detection and segmentation. It is a ground-up rewrite of the previous version, Detectron, and is powered by the PyTorch deep learning framework.