71 lines
2.2 KiB
Plaintext
71 lines
2.2 KiB
Plaintext
0.4.0a1
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=======
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* The paraphrase generation code was extended and can now use BART instead of GPT2. It also now
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has the ability to run as a translation task as well (using the Marian models) [#26, #27, #29, #31].
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* Added the ability to override the context and the question used as input to the model [#23].
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* MultiGPU training was tested and fixed [#25].
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* Completed support for beam search, including the ability to return multiple results for a given input [#30].
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* Misc bug fixes [#32].
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0.3.0
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=====
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* New option: sentence batching. Multiple sentences with related properties can be batched
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together in microbatches within a larger minibatch [#14, #11].
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* Added option to append context and question in a single model input [#18, #20, #22].
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* Updated Transformers dependency to 2.9, and fixed compatibility with newer versions [#18, #24].
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0.2.0
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=====
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* No changes since 0.2.0b2.
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Please see the development releases below for the full list of features in this release.
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0.2.0b2
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=======
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* Misc bug fixes related to inference time [#12, #13].
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0.2.0b1
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=======
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* Added multilingual Almond tasks [#10].
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0.2.0a2
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=======
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* Misc bug fixes [#8, #9]
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0.2.0a1
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=======
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New features:
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* Add new tasks for Almond: almond_dialogue_nlu, almond_dialogue_nlg, almond_dialogue_policy
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* Added a new encoder, "Coattention", which encodes the context and question separately, then
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coattends and applies a BiLSTM layer.
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* For Coattention and Identity encoder, it is now possible to specify the context and question
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embeddings separately.
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* Embeddings in context, question and answer can now be untied, by suffixing the name with '@'
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followed by an unique identifier (e.g. bert-base-uncased@0 and bert-base-uncased@1).
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* Added an option to pretrain the context encoder, using MLM objective.
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* Added beam search.
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* New embedding option: XLM-R (XLM trained with Roberta).
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* New task: paraphrasing with GPT2. This is not fully integrated with the other tasks yet,
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but it will in the future.
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* New command "genienlp export" can be used to save a trained model for inference.
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Incompatible changes:
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* The --save flag is now required when calling train
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0.1.1
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=====
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* Fix publishing on pypi
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0.1.0
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=====
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* First release
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