{"data":{"slug":"yongzhuo-keras-textclassification","name":"Keras-TextClassification","tagline":"Chinese text classification models based on Keras","github_url":"https://github.com/yongzhuo/Keras-TextClassification","owner":"yongzhuo","repo":"Keras-TextClassification","owner_avatar_url":"https://avatars.githubusercontent.com/u/31341349?v=4","primary_language":"Python","stars":1809,"forks":397,"topics":["albert","bert","capsule","charcnn","crnn","dcnn","dpcnn","embeddings","fasttext","han","keras","keras-textclassification","leam","nlp","rcnn","text-classification","textcnn","transformer","vdcnn","xlnet"],"archived":false,"github_pushed_at":"2024-06-17T22:45:14+00:00","maintenance_label":"Dormant","stars_delta_30d":-3,"url":"https://www.graphcanon.com/tools/yongzhuo-keras-textclassification","markdown_url":"https://www.graphcanon.com/tools/yongzhuo-keras-textclassification.md","api_url":"https://www.graphcanon.com/api/graphcanon/tools/yongzhuo-keras-textclassification","graph_url":"https://www.graphcanon.com/api/graphcanon/graph?tool=yongzhuo-keras-textclassification","description":"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","homepage_url":"https://blog.csdn.net/rensihui","license":"MIT","open_issues":4,"watchers":32,"ai_summary":"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.","readme_excerpt":"# Install(安装)\n\n```bash\npip install Keras-TextClassification\n```\n\n```python\nstep2: 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\n       cover the dir of data to anaconda, like '/anaconda/3.5.1/envs/tensorflow13/Lib/site-packages/keras_textclassification/data'\nstep3: goto # Train&Usage(调用) and Predict&Usage(调用)\n```","github_created_at":"2019-06-13T15:02:31+00:00","created_at":"2026-07-11T11:30:13.568755+00:00","updated_at":"2026-08-22T12:00:57.178187+00:00","categories":[{"slug":"model-training","name":"Model Training","url":"https://www.graphcanon.com/categories/model-training","markdown_url":"https://www.graphcanon.com/categories/model-training.md","api_url":"https://www.graphcanon.com/api/graphcanon/categories/model-training"}],"tags":[{"slug":"albert","name":"albert"},{"slug":"bert","name":"bert"},{"slug":"capsulenetwork","name":"capsulenetwork"},{"slug":"charcnn","name":"charcnn"},{"slug":"crnn","name":"crnn"},{"slug":"dcnn","name":"dcnn"},{"slug":"dpcnn","name":"dpcnn"},{"slug":"embeddings","name":"embeddings"}],"trust":{"provenance":{"is_fork":false,"github_id":191784463,"owner_type":"User","methodology":"github_public_v1","parent_repo":null,"near_duplicate_slugs":[]},"computed_at":"2026-08-22T12:00:56.065Z","maintenance":{"label":"Dormant","score":18,"methodology":"github_public_v1","releases_90d":0,"days_since_push":795,"last_release_at":"2020-12-19T16:49:04Z","stars_delta_30d":-3,"open_issues_delta_30d":0},"security_summary":{"status":"no_lockfile","scanner":null,"low_count":0,"high_count":0,"last_scan_at":"2026-07-11T11:30:14.817Z","medium_count":0,"scan_profile":"none","critical_count":0}},"capability_facts":{"scan":{"source":"repo_scan","observed_at":"2026-08-22T12:00:56.525Z"},"languages":{"value":["python"],"source":"github.language","observed_at":"2026-08-22T12:00:56.525Z"},"license_spdx":{"value":"MIT","source":"github.license","observed_at":"2026-08-22T12:00:56.525Z"}},"decision_facts":{"hosting":null,"pricing":null,"requirements":{"notes":["Python environment must be prepared for running Keras.","Supports multiple model types requiring different levels of computation resources."],"min_ram_gb":4,"requires_docker":false},"constraints":{"min_ram_gb":4,"requires_docker":false},"when_to_use":["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."],"when_not_to_use":["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."],"source":"enrich:decision_facts","observed_at":"2026-07-16T23:01:45.358Z"},"constraint_facets":{"min_ram_gb":4,"requires_docker":false},"decision_summary":[{"label":"Requirements","value":"Min 4 GB RAM; Python environment must be prepared for running Keras.; Supports multiple model types requiring different levels of computation resources."},{"label":"Adopt for","value":"Chinese-focused text classification models using Keras."},{"label":"License detail","value":"MIT License - allows free use, modification, distribution with attribution required but no guarantee or liability from contributors."}]}}