# flairNLP/flair

A very simple framework for state-of-the-art Natural Language Processing (NLP)

Repository: https://github.com/flairNLP/flair
Canonical: https://ross.abutalabs.com/products/flair
Homepage: https://flairnlp.github.io/flair/
Language: Python
License: NOASSERTION
License Family: other
Topics: pytorch, nlp, named-entity-recognition, sequence-labeling, semantic-role-labeling, word-embeddings, natural-language-processing, machine-learning
Last push: 2025-10-27T18:11:31+00:00

## Health v2 (maintenance only)
Score: 52/100 (v2, computed 2026-09-03T02:20:16.233290+00:00)
- activity 49, release rhythm 28, longevity 100
- inputs: {"age_days": 3005, "days_push": 310, "days_rel": 574, "gap_med": 47, "n_releases_24m": 2}
- flags: no_license
- formula: round(0.45*activity + 0.35*rhythm + 0.20*longevity); archived -> min(score, 10)

## Adoption (not part of the score)
Stars 14384, forks 2105 (observed 2026-08-28T04:11:06.898583+00:00)

## What it is
Flair is a Python NLP framework built on PyTorch for state-of-the-art natural language processing tasks such as named entity recognition, part-of-speech tagging, sentiment analysis, and text classification. It also serves as a text embedding library, letting users combine word and document embeddings including its own Flair embeddings and transformer models.

## Use cases
- extract named entities from text
- train a custom NER model
- tag part-of-speech in sentences
- classify text sentiment
- compute word and document embeddings
- run NLP on biomedical texts
- fine-tune transformer models for sequence labeling

## When to choose
- you need ready-to-use state-of-the-art NER or tagging models in Python
- you want a simple PyTorch-based API to train custom sequence labeling models
- you need multilingual NLP support or biomedical text models
- you want to combine multiple embedding types easily

## When to avoid
- you need a lightweight production inference server rather than a training framework
- you prefer lower-level control over model internals than the framework abstraction allows
- your project is not Python/PyTorch based

## Facets
- artifact type: library
- maturity: active
- function: nlp, machine-learning, deep-learning
- domain: machine-learning, deep-learning
- platform: python
- tags: pytorch, named-entity-recognition, sequence-labeling, word-embeddings, text-classification, transformers, biomedical-nlp, natural-language-processing

## Member repositories
- flairNLP/flair (main) score 52

## Provenance
- Observed fields: from GitHub, fetched 2026-08-28T04:11:06.898583+00:00.
- Health v2: computed from the inputs above; adoption is never an input.
- Inferred fields (summary, facets, guidance): AI-extracted, prompt v1, taxonomy v1, on 2026-08-29T17:12:36.761176+00:00, confidence not recorded.
  - readme: https://github.com/flairNLP/flair (fetched 2026-08-28T04:11:06.898583+00:00, sha 430534d069f0)
  - homepage: https://flairnlp.github.io/flair/ (fetched 2026-08-29T08:06:04.842063+00:00, sha 2dad3798d720)
  - registry_pypi: https://pypi.org/pypi/flair/json (fetched 2026-08-29T08:06:04.851253+00:00, sha 40ccb66bca13)
- Data as of 2026-08-30T08:39:29.467469+00:00.