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Quick README update

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Anthony MOI
2020-01-08 14:07:48 -05:00
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README.md
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@ -5,8 +5,7 @@ versatility.
## What is a Tokenizer
A Tokenizer works as a pipeline, it processes some raw text as input and outputs an
`Encoding`.
A Tokenizer works as a pipeline, it processes some raw text as input and outputs an `Encoding`.
The various steps of the pipeline are:
1. The `Normalizer`: in charge of normalizing the text. Common examples of normalization are
@ -18,6 +17,17 @@ The various steps of the pipeline are:
4. The `PostProcessor`: in charge of post-processing the `Encoding` to add anything relevant
that, for example, a language model would need, such as special tokens.
## Main features:
- Train new vocabularies and tokenize, using todays most used tokenizers.
- Extremely fast (both training and tokenization), thanks to the Rust implementation. Takes
less than 20 seconds to tokenize a GB of text on a server's CPU.
- Easy to use, but also extremely versatile.
- Designed for research and production.
- Normalization comes with alignments tracking. It's always possible to get the part of the
original sentence that corresponds to a given token.
- Does all the pre-processing: Truncate, Pad, add the special tokens your model needs.
## Bindings
We provide bindings to the following languages (more to come!):