[FEATURE] Upgrade tokenizer and add new pretrained model: W2V

[KenelmQLH]

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Description

1. add PureTextToeknizer and TextTokenizer for get_tokenizer
2. add W2V for get_pretained_i2v

What does this implement/fix? Explain your changes.

N/A

Pull request type

• [DATASET] Add a new dataset
• [BUGFIX] Bugfix
• [FEATURE] New feature (non-breaking change which adds functionality)
• [BREAKING] Breaking change (fix or feature that would cause existing functionality to not work as expected)
• [STYLE] Code style update (formatting, renaming)
• [REFACTOR] Refactoring (no functional changes, no api changes)
• [BUILD] Build related changes
• [DOC] Documentation content changes
• [OTHER] Other (please describe):

Changes

N/A

Does this close any currently open issues?

N/A

Any relevant logs, error output, etc?

N/A

Checklist

Before you submit a pull request, please make sure you have to following:

Essentials

• PR's title starts with a category (e.g. [BUGFIX], [FEATURE], [BREAKING], [DOC], etc)
• Changes are complete (i.e. I finished coding on this PR)
• All changes have test coverage and al tests passing
• Code is well-documented (extended the README / documentation, if necessary)
• If this PR is your first one, add your name and github account to AUTHORS.md

Comments

• If this change is a backward incompatible change, why must this change be made.
• Interesting edge cases to note here

[codecov-commenter]

Codecov Report

Merging #43 (61ef101) into master (51bbf2e) will increase coverage by 0.00%.
The diff coverage is 100.00%.

@@           Coverage Diff           @@
##           master      #43   +/-   ##
=======================================
  Coverage   99.85%   99.85%           
=======================================
  Files          46       46           
  Lines        1338     1363   +25     
=======================================
+ Hits         1336     1361   +25     
  Misses          2        2           

Impacted Files	Coverage Δ
EduNLP/I2V/__init__.py	100.00% <100.00%> (ø)
EduNLP/I2V/i2v.py	100.00% <100.00%> (ø)
EduNLP/SIF/tokenization/tokenization.py	99.12% <100.00%> (+0.01%)	⬆️
EduNLP/Tokenizer/tokenizer.py	100.00% <100.00%> (ø)
EduNLP/Vector/t2v.py	100.00% <100.00%> (ø)

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