get_tokenizer

Sure, the `get_tokenizer()` function is a method provided by the Hugging Face's `transformers` library. It is used to retrieve the tokenizer associated with a specific pre-trained model. This tokenizer is responsible for converting raw text into a sequence of tokens that can be understood by the model.

Here's an example of how to use `get_tokenizer()`:

from transformers import AutoTokenizer

model_name = "bert-base-uncased"
tokenizer = AutoTokenizer.from_pretrained(model_name)

# Retrieve the tokenizer associated with the model
tokenizer = tokenizer.get_tokenizer()

In this example, we first load a pre-trained model called "bert-base-uncased" using `AutoTokenizer.from_pretrained()`. Then, we use `get_tokenizer()` to retrieve the tokenizer object associated with the model.

Please note that the code example above assumes you have already installed the `transformers` library. You can install it by running `pip install transformers` in your Python environment.