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Demo: demo
Rust document: docs.rs
Blog post: How to calculate the alignment between BERT and spaCy tokens effectively and robustly
- Installation
$ pip install -U pip # update pip
$ pip install pytokenizations- Or, install from source
This library uses maturin to build the wheel.
$ git clone https://github.com/tamuhey/tokenizations $ cd tokenizations/python $ pip install maturin $ maturin build
Now the wheel is created in python/target/wheels directory, and you can install it with pip install *whl.
def get_alignments(a: Sequence[str], b: Sequence[str]) -> Tuple[List[List[int]], List[List[int]]]: ...
Returns alignment mappings for two different tokenizations:
>>> tokens_a = ["å", "BC"] >>> tokens_b = ["abc"] # the accent is dropped (å -> a) and the letters are lowercased(BC -> bc) >>> a2b, b2a = tokenizations.get_alignments(tokens_a, tokens_b) >>> print(a2b) [[0], [0]] >>> print(b2a) [[0, 1]]
a2b[i] is a list representing the alignment from tokens_a to tokens_b.
See here: docs.rs
- Algorithm overview
- Blog post
- seqdiff is used for the diff process.
- textspan
- explosion/spacy-alignments: 💫 A spaCy package for Yohei Tamura's Rust tokenizations library
- Python bindings for this library, maintained by Explosion, author of spaCy. If you feel difficult to install pytokenizations, please try this.