# Use tokenizers from 🤗 Tokenizers

The [`PreTrainedTokenizerFast`] depends on the [🤗 Tokenizers](https://huggingface.co/docs/tokenizers) library. The tokenizers obtained from the 🤗 Tokenizers library can be

loaded very simply into 🤗 Transformers.

Before getting in the specifics, let's first start by creating a dummy tokenizer in a few lines:

thon

>>> from tokenizers import Tokenizer

>>> from tokenizers.models import BPE

>>> from tokenizers.trainers import BpeTrainer

>>> from tokenizers.pre_tokenizers import Whitespace

>>> tokenizer = Tokenizer(BPE(unk_token="[UNK]"))

>>> trainer = BpeTrainer(special_tokens=["[UNK]", "[CLS]", "[SEP]", "[PAD]", "[MASK]"])

>>> tokenizer.pre_tokenizer = Whitespace()

>>> files = []

>>> tokenizer.train(files, trainer)

We now have a tokenizer trained on the files we defined. We can either continue using it in that runtime, or save it to

a JSON file for future re-use.

## Loading directly from the tokenizer object

Let's see how to leverage this tokenizer object in the 🤗 Transformers library. The

[`PreTrainedTokenizerFast`] class allows for easy instantiation, by accepting the instantiated

*tokenizer* object as an argument:

thon

>>> from transformers import PreTrainedTokenizerFast

>>> fast_tokenizer = PreTrainedTokenizerFast(tokenizer_object=tokenizer)

This object can now be used with all the methods shared by the 🤗 Transformers tokenizers! Head to [the tokenizer

page](main_classes/tokenizer) for more information.

## Loading from a JSON file

In order to load a tokenizer from a JSON file, let's first start by saving our tokenizer:

thon

>>> tokenizer.save("tokenizer.json")

The path to which we saved this file can be passed to the [`PreTrainedTokenizerFast`] initialization

method using the `tokenizer_file` parameter:

thon

>>> from transformers import PreTrainedTokenizerFast

>>> fast_tokenizer = PreTrainedTokenizerFast(tokenizer_file="tokenizer.json")

This object can now be used with all the methods shared by the 🤗 Transformers tokenizers! Head to [the tokenizer

page](main_classes/tokenizer) for more information.