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Releases: BrikerMan/Kashgari

v0.5.4

30 Sep 14:21
cf5b6dc
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  • ✨ 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

v0.5.3

11 Aug 15:39
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  • 🐛 Fixing CuDNN Error (#198)

v0.5.2

10 Aug 06:25
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  • 💥 Add CuDNN Cell config, disable auto CuDNN cell. (#182, #198)

v0.5.1

15 Jul 11:00
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  • 📝 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)

v0.2.6 (legacy version)

12 Jul 10:07
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  • 📝 Add tf.keras version info
  • 🐛 Fixing lstm issue in labeling model (#125)

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v0.5.0

11 Jul 10:24
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🎉🎉 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.

v0.2.4

06 Jun 09:55
90fcd52
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  • 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.

release v0.2.1

05 Mar 09:01
6a75f15
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  • fix missing sequence_labeling_tokenize_add_bos_eos consig

release v0.2.0

05 Mar 08:54
647c8c4
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release v0.2.0 Pre-release
Pre-release
  • 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

release v0.1.9

28 Feb 03:15
26f85b0
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  • add AVCNNModel, KMaxCNNModel, RCNNModel, AVRNNModel, DropoutBGRUModel, DropoutAVRNNModel model to classification task.
  • fix several small bugs