Thinc
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Overview
HEALTH SCORE
Fair
54out of 100
Development cadence drags the score down. Maintainer coverage and security posture help keep it from falling further.
LIFECYCLE
Stable
Mature and deliberately low-activity. The maintainer is reachable and there are no open issues or vulnerabilities that require attention.
Health breakdown
Fair(54/100)
Maintainer availability, known risks and supply chain posture, and whether the project is actively developed or appropriately stable.
Maintainer responsiveness
Median response time is 19 days.
Bus factor
5 active maintainers currently have merge rights.
Organization Diversity
Contributors span 22 organizations.
Project Achievements
Leaderboards
About
Thinc is a lightweight deep learning library that offers a functional approach to neural network layers, designed to be composable and interoperable with PyTorch, TensorFlow and MXNet. It provides a clean, hackable machine learning framework used extensively in spaCy's natural language processing models.
First commit
Software value
$1.7M
Tags
ai
artificial-intelligence
deep-learning
functional-programming
jax
machine-learning
machine-learning-library
mxnet
natural-language-processing
nlp
python
pytorch
spacy
tensorflow
type-checking
License(s)
MIT
Data sources
Git
GitHub