Kashgari Versions Save

• ✨ Add shuffle parameter to fit function (#249 )
• ✨ Improved type hinting for the loaded model (#248)
• 🐛 Fix loading models with CRF layers (#244, #228)
• 🐛 Fix the configuration changes during embedding save/load (#224)
• 🐛 Fix stacked embedding save/load (#224)
• 🐛 Fix evaluate function where the list has int instead of str (#222)
• 💥 Renaming model.pre_processor to model.processor
• 🚨 Removing TensorFlow and numpy warnings
• 📝 Add docs how to specify which CPU or GPU
• 📝 Add docs how to compile model with custom optimizer

• 🐛 Fixing CuDNN Error (#198)

• 💥 Add CuDNN Cell config, disable auto CuDNN cell. (#182, #198)

• 📝 Rewrite documents with mkdocs
• 📝 Add Chinese documents
• ✨ Add predict_top_k_class for classification model to get predict probabilities (#146)
• 🚸 Add label2idx, token2idx properties to Embeddings and Models
• 🚸 Add tokenizer property for BERT Embedding. (#136)
• 🚸 Add predict_kwargs for models predict() function
• ⚡️ Change multi-label classification's default loss function to binary_crossentropy (#151)

• 📝 Add tf.keras version info
• 🐛 Fixing lstm issue in labeling model (#125)

Code Compare

🎉🎉 tf.keras version 🎉🎉

• 🎉 Rewrite Kashgari using tf.keras. Discussion: #77
• 🎉 Rewrite Documents.
• ✨ Add TPU support.
• ✨ Add TF-Serving support.
• ✨ Add advance customization support, like multi-input model.
• 🐎 Performance optimization.

• Add BERT output feature layer finetune support. Discussion: #103
• Add BERT output feature layer number selection, default 4 according to BERT paper.
• Fix BERT embedding token index offset issue #104.

• fix missing sequence_labeling_tokenize_add_bos_eos consig

• multi-label classification for all classification models
• support cuDNN cell for sequence labeling
• add option for output BOS and EOS in sequence labeling result, fix #31

• add AVCNNModel, KMaxCNNModel, RCNNModel, AVRNNModel, DropoutBGRUModel, DropoutAVRNNModel model to classification task.
• fix several small bugs