# yongzhuo/Keras-TextClassification

中文长文本分类、短句子分类、多标签分类、两句子相似度（Chinese Text Classification of Keras NLP, multi-label classify, or sentence classify, long or short），字词句向量嵌入层（embeddings）和网络层（graph）构建基类，FastText，TextCNN，CharCNN，TextRNN,  RCNN,  DCNN, DPCNN, VDCNN, CRNN, Bert, Xlnet, Albert, Attention, DeepMoji, HAN, 胶囊网络-CapsuleNet, Transformer-encode,  Seq2seq,  SWEM, LEAM, TextGCN

Repository: https://github.com/yongzhuo/Keras-TextClassification
Canonical: https://ross.abutalabs.com/products/keras-textclassification
Homepage: https://blog.csdn.net/rensihui
Language: Python
License: MIT
License Family: permissive
Topics: text-classification, keras, rcnn, dcnn, charcnn, bert, nlp, textcnn, fasttext, dpcnn, embeddings, capsule, vdcnn, crnn, han, xlnet, albert, keras-textclassification, leam, transformer
Last push: 2024-06-17T22:45:14+00:00

## Health v2 (maintenance only)
Score: 23/100 (v2, computed 2026-09-03T02:20:16.233290+00:00)
- activity 0, release rhythm 8, longevity 100
- inputs: {"age_days": 2638, "days_push": 807, "days_rel": null, "gap_med": null, "n_releases_24m": 0}
- flags: none
- formula: round(0.45*activity + 0.35*rhythm + 0.20*longevity); archived -> min(score, 10)

## Adoption (not part of the score)
Stars 1808, forks 397 (observed 2026-08-28T04:05:39.345405+00:00)

## What it is
A Keras-based library for Chinese text classification supporting long/short text, multi-label classification, and sentence pair similarity. It implements many models (FastText, TextCNN, TextRNN, RCNN, DPCNN, BERT, XLNet, ALBERT, HAN, CapsuleNet, Transformer, etc.) with pluggable embedding layers (word2vec, BERT, random).

## Use cases
- classify chinese text into categories
- train a multi-label text classifier
- compute similarity between two sentences
- compare textcnn vs bert for text classification
- fine-tune bert for chinese text classification
- build a fasttext classifier in keras

## When to choose
- you need Chinese text classification with many model architectures to compare
- you want multi-label classification or sentence similarity in Keras
- you want to experiment with classic text classification models like TextCNN, DPCNN, HAN

## When to avoid
- you need PyTorch or modern transformer tooling like HuggingFace
- you work with non-Chinese text primarily
- you need actively developed, production-grade NLP pipelines

## Facets
- artifact type: library
- maturity: maintenance
- function: machine-learning, nlp, deep-learning
- domain: machine-learning, deep-learning
- platform: python
- tags: text-classification, keras, chinese-nlp, bert, textcnn, multi-label-classification, sentence-similarity, embeddings, natural-language-processing

## Member repositories
- yongzhuo/Keras-TextClassification (main) score 23

## Provenance
- Observed fields: from GitHub, fetched 2026-08-28T04:05:39.345405+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 2026-08-30T03:21:24.995295+00:00, confidence not recorded.
  - readme: https://github.com/yongzhuo/Keras-TextClassification (fetched 2026-08-28T04:05:39.345405+00:00, sha 6f4caf8fbb28)
  - homepage: https://blog.csdn.net/rensihui (fetched 2026-08-29T11:00:32.217249+00:00, sha 4c771860b30f)
  - registry_pypi: https://pypi.org/pypi/keras-textclassification/json (fetched 2026-08-29T11:00:32.221900+00:00, sha fc3427a8b2f9)
- Data as of 2026-08-30T08:39:29.467469+00:00.