✨ prodigy v1.14.5Oct 24, 2023Toggle for character vs. token highlighting, CSS and JS from local and remote paths
🤖 curated-transformers v1.3.0Oct 2, 2023Custom model repositories, NVTX Ranges, store config in models
Introducing spaCy v3.6spaCy v3.6 introduces the span finder component and trained pipelines for Slovenian.
✨ prodigy v1.12.0Jul 5, 2023LLM-assisted workflows for annotation and prompt engineering, task routing for multi-annotator setups
Introducing spaCy v3.3spaCy v3.3 improves the speed of core pipeline components, adds a new trainable lemmatizer, and introduces trained pipelines for Finnish, Korean and Swedish.
🌸 floret v0.10.0Oct 27, 2021fastText + Bloom embeddings for compact, full-coverage vectors with spaCy
Introducing spaCy v2.3spaCy now speaks Chinese, Japanese, Danish, Polish and Romanian! Version 2.3 of the spaCy Natural Language Processing library adds models for five new languages. We've also updated all 15 model families with word vectors and improved accuracy, while also decreasing model size and loading times for models with vectors.
✨ prodigy v1.16.0Oct 22, 2024Modal plugin for on-demand deployment, cross-platform wheels and UI fixes
spaCy Plugin for VSCodeThe spaCy VSCode Extension provides additional tooling and features for working with spaCy’s config files. Version 1.0.0 includes hover descriptions for registry functions, variables, and section names within the config as an installable extension.
Introducing spaCy v3.2spaCy v3.2 features usability improvements for custom training and scoring, improved performance and support for floret, our new fastText word vectors algorithm.
🛸 spacy-transformers v1.1.0Oct 18, 2021Better serialization, full ModelOutput, mixed-precision training and more
✨ prodigy v1.10.0Jun 16, 2020Dependency and relation annotation, audio, video, character-based NER & more
Introducing spaCy v2.2Version 2.2 of the spaCy Natural Language Processing library is leaner, cleaner and even more user-friendly. In addition to new model packages and features for training, evaluation and serialization, we've made lots of bug fixes, improved debugging and error handling, and greatly reduced the size of the library on disk.
✨ prodigy v1.8.0May 20, 2019Support for spaCy v2.1, basic auth, multi-user sessions, review workflow & more
✨ prodigy v1.17.0Nov 18, 2024Pages UI for multi-page tasks like longer documents, PDFs or collections of images
✨ prodigy v1.14.3Oct 6, 2023Inter-annotator agreement for document-level and token-level annotations, new plugins
🦙 spacy-llm v0.3.0Jun 14, 2023Cohere, Anthropic, OpenLLaMa, StableLM, logging, streamlit demo, lemmatization task
Introducing spaCy v3.5spaCy v3.5 introduces new CLI commands, fuzzy matching, improvements for entity linking and more.
✨ prodigy v1.11.0Aug 12, 2020spaCy v3 support, annotation for overlapping and nested spans, better installation & more
Introducing spaCy v3.1It’s been great to see the adoption of spaCy v3, which introduced transformer-based pipelines, a new training system and more. Version 3.1 adds more on top of it, including the ability to use predicted annotations during training, a component for predicting arbitrary and overlapping spans and new pipelines for Catalan and Danish.
Introducing spaCy v2.1Version 2.1 of the spaCy Natural Language Processing library includes a huge number of features, improvements and bug fixes. In this post, we highlight some of the things we're especially pleased with, and explain some of the most challenging parts of preparing this big release.
🦙 spacy-llm v0.5.0Sep 8, 2023Improved user API and novel Chain-of-Thought prompting for more accurate NER
Introducing spaCy v3.4spaCy v3.4 brings typing and speed improvements along with new vectors for English CNN pipelines and new trained pipelines for Croatian.
Introducing spaCy v3.0spaCy v3.0 is a huge release! It features new transformer-based pipelines that get spaCy's accuracy right up to the current state-of-the-art, and a new workflow system to help you take projects from prototype to production. It's much easier to configure and train your pipeline, and there are lots of new and improved integrations with the rest of the NLP ecosystem.
Introducing spaCyComputers don't understand text. This is unfortunate, because that's what the web almost entirely consists of. We want to recommend people text based on other text they liked. We want to shorten text to display it on a mobile screen. We want to aggregate it, link it, filter it, categorise it, generate it and correct it. spaCy provides a library of utility functions that help programmers build such products.