To upgrade Kashgari to the latest version, use pip
:
pip uninstall -y kashgari-tf
pip install --upgrade kashgari
To inspect the currently installed version, use the following command:
pip show kashgari
- 🐛 Fixing vocab_path typo.
- ✨ Add save best model callback
KashgariModelCheckpoint
. - ⬆️ Upgrading
bert4keras
version to0.6.5
.
1.1.1 - 2020.03.13
- ✨ Add BERTEmbeddingV2.
- 💥 Migrate documents to https://readthedoc.org for the version control.
1.1.0 - 2019.12.27
- ✨ Add Scoring task. (#303)
- ✨ Add tokenizers.
- 🐛 Fixing multi-label classification model loading. #304
1.0.0 - 2019.10.18
Unfortunately, we have to change the package name for clarity and consistency. Here is the new naming sytle.
Backend | pypi version | desc |
---|---|---|
TensorFlow 2.x | kashgari 2.x.x | coming soon |
TensorFlow 1.14+ | kashgari 1.x.x | |
Keras | kashgari 0.x.x | legacy version |
Here is how the existing versions changes
Supported Backend | Kashgari Versions | Kahgsari-tf Version |
---|---|---|
TensorFlow 2.x | kashgari 2.x.x | - |
TensorFlow 1.14+ | kashgari 1.0.1 | - |
TensorFlow 1.14+ | kashgari 1.0.0 | 0.5.5 |
TensorFlow 1.14+ | - | 0.5.4 |
TensorFlow 1.14+ | - | 0.5.3 |
TensorFlow 1.14+ | - | 0.5.2 |
TensorFlow 1.14+ | - | 0.5.1 |
Keras (legacy) | kashgari 0.2.6 | - |
Keras (legacy) | kashgari 0.2.5 | - |
Keras (legacy) | kashgari 0.x.x | - |
0.5.4 - 2019.09.30
- ✨ Add shuffle parameter to fit function (#249)
- ✨ Improved type hinting for 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
0.5.3 - 2019.08.11
- 🐛 Fixing CuDNN Error (#198)
0.5.2 - 2019.08.10
0.5.1 - 2019.07.15
- 📝 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 modelspredict()
function - ⚡️ Change multi-label classification's default loss function to binary_crossentropy (#151)
0.5.0 - 2019.07.11
🎉🎉 tf.keras version 🎉🎉
- 🎉 Rewrite Kashgari using
tf.keras
(#77) - 🎉 Rewrite Documents
- ✨ Add TPU support
- ✨ Add TF-Serving support.
- ✨ Add advance customization support, like multi-input model
- 🐎 Performance optimization
0.2.6 - 2019.07.12
- 📝 Add tf.keras version info
- 🐛 Fixing lstm issue in labeling model (#125)
0.2.4 - 2019.06.06
- Add BERT output feature layer fine-tune support. Discussion: (#103)
- Add BERT output feature layer number selection, default 4 according to BERT paper
- Fix BERT embedding token index offset issue (#104
0.2.1 - 2019.03.05
- fix missing
sequence_labeling_tokenize_add_bos_eos
config
- multi-label classification for all classification models
- support cuDNN cell for sequence labeling
- add option for output
BOS
andEOS
in sequence labeling result, fix #31
- add
AVCNNModel
,KMaxCNNModel
,RCNNModel
,AVRNNModel
,DropoutBGRUModel
,DropoutAVRNNModel
model to classification task. - fix several small bugs
- fix BERT Embedding model's
to_json
function, issue #19
- remove class candidates filter to fix #16
- overwrite init function in CustomEmbedding
- add parameter check to custom_embedding layer
- add
keras-bert
version to setup.py file
- add
output_dict
,debug_info
params to text_classification model - add
output_dict
,debug_info
andchunk_joiner
params to text_classification model - fix possible crash at data_generator
- fix sequence labeling evaluate result output
- refactor model save and load function
- fix classification model evaluate result output
- change test settings