Python v0.11.1

[#860] Adding TruncationSide to TruncationParams.

Python v0.11.0

Fixed

• [#585] Conda version should now work on old CentOS
• [#844] Fixing interaction between is_pretokenized and trim_offsets.
• [#851] Doc links

Added

• [#657]: Add SplitDelimiterBehavior customization to Punctuation constructor
• [#845]: Documentation for Decoders.

Changed

• [#850]: Added a feature gate to enable disabling http features
• [#718]: Fix WordLevel tokenizer determinism during training
• [#762]: Add a way to specify the unknown token in SentencePieceUnigramTokenizer
• [#770]: Improved documentation for UnigramTrainer
• [#780]: Add Tokenizer.from_pretrained to load tokenizers from the Hugging Face Hub
• [#793]: Saving a pretty JSON file by default when saving a tokenizer

Node v0.8.0

BREACKING CHANGES

• Many improvements on the Trainer (#519).
  The files must now be provided first when calling tokenizer.train(files, trainer).

Features

• Adding the TemplateProcessing
• Add WordLevel and Unigram models (#490)
• Add nmtNormalizer and precompiledNormalizer normalizers (#490)
• Add templateProcessing post-processor (#490)
• Add digitsPreTokenizer pre-tokenizer (#490)
• Add support for mapping to sequences (#506)
• Add splitPreTokenizer pre-tokenizer (#542)
• Add behavior option to the punctuationPreTokenizer (#657)
• Add the ability to load tokenizers from the Hugging Face Hub using fromPretrained (#780)

Fixes

• Fix a bug where long tokenizer.json files would be incorrectly deserialized (#459)
• Fix RobertaProcessing deserialization in PostProcessorWrapper (#464)

Python v0.10.3

Fixed

• [#686]: Fix SPM conversion process for whitespace deduplication
• [#707]: Fix stripping strings containing Unicode characters

Added

• [#693]: Add a CTC Decoder for Wave2Vec models

Removed

• [#714]: Removed support for Python 3.5

Python v0.10.2

Fixed

• [#652]: Fix offsets for Precompiled corner case
• [#656]: Fix BPE continuing_subword_prefix
• [#674]: Fix Metaspace serialization problems

Python v0.10.1

Fixed

• [#616]: Fix SentencePiece tokenizers conversion
• [#617]: Fix offsets produced by Precompiled Normalizer (used by tokenizers converted from SPM)
• [#618]: Fix Normalizer.normalize with PyNormalizedStringRefMut
• [#620]: Fix serialization/deserialization for overlapping models
• [#621]: Fix ByteLevel instantiation from a previously saved state (using __getstate__())

Python v0.10.0

Added

• [#508]: Add a Visualizer for notebooks to help understand how the tokenizers work
• [#519]: Add a WordLevelTrainer used to train a WordLevel model
• [#533]: Add support for conda builds
• [#542]: Add Split pre-tokenizer to easily split using a pattern
• [#544]: Ability to train from memory. This also improves the integration with datasets
• [#590]: Add getters/setters for components on BaseTokenizer
• [#574]: Add fust_unk option to SentencePieceBPETokenizer

Changed

• [#509]: Automatically stubbing the .pyi files
• [#519]: Each Model can return its associated Trainer with get_trainer()
• [#530]: The various attributes on each component can be get/set (ie.
  tokenizer.model.dropout = 0.1)
• [#538]: The API Reference has been improved and is now up-to-date.

Fixed

• [#519]: During training, the Model is now trained in-place. This fixes several bugs that were
  forcing to reload the Model after a training.
• [#539]: Fix BaseTokenizer enable_truncation docstring

Python v0.10.0rc1

Added

• [#508]: Add a Visualizer for notebooks to help understand how the tokenizers work
• [#519]: Add a WordLevelTrainer used to train a WordLevel model
• [#533]: Add support for conda builds
• [#542]: Add Split pre-tokenizer to easily split using a pattern
• [#544]: Ability to train from memory. This also improves the integration with datasets

Changed

• [#509]: Automatically stubbing the .pyi files
• [#519]: Each Model can return its associated Trainer with get_trainer()
• [#530]: The various attributes on each component can be get/set (ie.
  tokenizer.model.dropout = 0.1)
• [#538]: The API Reference has been improved and is now up-to-date.

Fixed

• [#519]: During training, the Model is now trained in-place. This fixes several bugs that were
  forcing to reload the Model after a training.
• [#539]: Fix BaseTokenizer enable_truncation docstring

Python v0.9.4

Fixed

• [#492]: Fix from_file on BertWordPieceTokenizer
• [#498]: Fix the link to download sentencepiece_model_pb2.py
• [#500]: Fix a typo in the docs quicktour

Changed

• [#506]: Improve Encoding mappings for pairs of sequence

Python v0.9.3

Fixed

• [#470]: Fix hanging error when training with custom component
• [#476]: TemplateProcessing serialization is now deterministic
• [#481]: Fix SentencePieceBPETokenizer.from_files

Added

• [#477]: UnicodeScripts PreTokenizer to avoid merges between various scripts
• [#480]: Unigram now accepts an initial_alphabet and handles special_tokens correctly