Keras-TextClassification
Chinese text classification models based on Keras
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Decision brief
Chinese-focused text classification models using Keras.
Good fit when
- Requires Chinese text classification for tasks like multi-label, sentence similarity analysis.
- Needs a variety of neural net architectures including FastText, CNNs, RNNs and Transformers for flexibility.
Avoid when
- Does not cater to non-Chinese language datasets effectively due to its Chinese-specific models.
- Avoid if you seek a tool with extensive support beyond text classification like NER or POS tagging.
- Requirements:
- Min 4 GB RAM; Python environment must be prepared for running Keras.; Supports multiple model types requiring different levels of computation resources.
Observed Jul 16, 2026 · Source: enrich:decision_facts
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Maintenance and security
Full trust report- Maintenance
- Dormant (795d since push)
- As of today
- Provenance
- Not a fork · Personal account
- As of today
- Security (OSV)
- No lockfile
- As of 1mo
Public GitHub metadata and optional OSV scans. Signals, not a guarantee. Trust methodology.
Install
pip install Keras-TextClassificationSimilar tools
Same-category neighbours. No typed graph edges are catalogued for this tool yet.
Evidence and technical details
Sourced facts, taxonomy, compatibility claims, README excerpt, and machine-readable endpoints.
Overview
Provides multiple neural network architectures for text classification tasks including multi-label and sentence similarity analysis. Models include FastText, CNNs (CharCNN, TextCNN), RNNs, Transformers, BERT, XLNet, and more.
Capability facts
- Languages
- python
Source: github.language · Aug 22, 2026
Categories
Compatibility
Sourced claims from the README excerpt - not unsourced marketing copy.
Source: README excerpt (regex_v1, Aug 22, 2026)
```python step2: download and unzip the dir of 'data.rar', 地址: 链接：https://pan.baidu.com/s/Source link
Tags
README
Install(安装)
pip install Keras-TextClassification
step2: download and unzip the dir of 'data.rar', 地址: 链接：https://pan.baidu.com/s/1pIDzGaGXCZ7cjng1XU_kPA 提取码：w6ps 压缩包密码: 2022
cover the dir of data to anaconda, like '/anaconda/3.5.1/envs/tensorflow13/Lib/site-packages/keras_textclassification/data'
step3: goto # Train&Usage(调用) and Predict&Usage(调用)
For agents
This page has a .md twin and JSON over the API.