Explosion Developer Tools

Explosion builds developer tools for AI, Machine Learning, and Natural Language Processing.

Project

• spaCy
• Prodigy
• Ellf
• Thinc

Topics

• LLMs
• NLP Strategy
• Annotation
• Biomedical
• Finance
• Media
• Legal
• Humanities
• Computer Vision

Category

• Blog
• Release
• Universe
• Talk
• Interview
• Video
• Paper
• Book

Tasks

Select... Code Generation, Coreference Resolution, Dependency Parsing, Distillation, Embeddings & Vectors, Entity Linking, Evaluation, Image Classification, Image Segmentation, Layout Analysis, Lemmatization, Named Entity Recognition, Object Detection, Optical Character Recognition (OCR), Part-of-Speech Tagging, PII Anonymization, Question Answering, Relation Extraction, Retrieval-Augmented Generation (RAG), Rule-Based Matching, Span Categorization, Text Classification, Text Generation, Tokenization, Weak Supervision

Authors

Select... Adriane Boyd, Ákos Kádár, Basile Dura, Chung-Fan Tsai, Damian Romero, Daniel de Kok, Duygu Altinok, Edward Schmuhl, Helena Steckmeister, India Kerle, Ines Montani, Kabir Khan, Lj Miranda, Madeesh Kannan, Magdalena Anioł, Matthew Honnibal, Paul O’Leary McCann, Peter Baumgartner, Philip Vollet, Raphael Mitsch, Rehan Ahmed, Richard Hudson, Ryan Wesslen, Sofie Van Landeghem, Victoria Slocum, Vincent D. Warmerdam, Vinit Ravishankar, Walter Henry

Video Series

Streaming spaCy

Join spaCy author and core developer Matt as he works on the library, develops features, and fixes bugs, while chatting about all things NLP and open source. Every Thursday at 2pm CET and Friday at 11am CET.

Task Routers in Prodigy

How to use the new task routers to customize how examples are assigned in multi-annotator workflows.

Finding Video Games with Sense2Vec

In this video, we’ll show how you can improve the annotation experience by leveraging sense2vec to pre-fill named entities.

Finding Duplicates in Tabular Data with Jupyter and Prodigy

In this video, we’ll show you how to use Prodigy to train a named entity recognition model from scratch, by taking advantage of semi-automatic annotation and modern transfer learning techniques.

Prodigy v1.10: Dependencies, relations, audio, video & more

Version 1.10 of Prodigy includes tons of new features, including manual dependency and relation annotation, audio and video annotation, a new and improved image UI, new recipe callbacks, more settings for manual NER, plus various new config options and settings.

Intro to NLP with spaCy (4): Detecting programming languages

Training a new entity type with Prodigy – annotation powered by active learning

In this video, we’ll show you how to use Prodigy to train a phrase recognition system for a new concept. Specifically, we’ll train a model to detect references to drugs, using text from Reddit.

Image Captioning with Prodigy & PyTorch

In this video, we’ll show you how you can use Prodigy to script fully custom annotation workflows in Python, how to plug in your own machine learning models, and how to mix and match different interfaces for your specific use case.

spaCy v3: Custom trainable relation extraction component

spaCy v3.0 features new transformer-based pipelines that get spaCy’s accuracy right up to the current state-of-the-art, and a new training config and workflow system to help you take projects from prototype to production.