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Added TensorFlow module + BERT model #355
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Codecov Report
@@ Coverage Diff @@
## master #355 +/- ##
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- Coverage 80.29% 78.77% -1.53%
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Files 339 342 +3
Lines 11240 11537 +297
Branches 374 367 -7
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+ Hits 9025 9088 +63
- Misses 2215 2449 +234
Continue to review full report at Codecov.
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I think it makes sense to replace BERT with ALBERT - https://ai.googleblog.com/2019/12/albert-lite-bert-for-self-supervised.html |
This isn't going anywhere. Closing for now. |
Related issues
TransmogrifAI supports neither training nor inferencing deep learning models #248
Describe the proposed solution
Add additional TensorFlow module
Add ability to create, load and run TensorFlow models
Add BERT model
Compare with JohnSnow performance - https://github.com/JohnSnowLabs/spark-nlp/blob/master/src/main/scala/com/johnsnowlabs/nlp/embeddings/BertEmbeddings.scala. Update: JohnSnow dev team investigation is here - Performance of BertEmbeddings model JohnSnowLabs/spark-nlp#570
TBD BERT model inference is very slow. Additional investigation is required. And since JohnSnow library works better, perhaps we should wrap around it?
Describe alternatives you've considered
NA