Fix typos (#25936)
* fix typo * fix typo * fix typo * fix typos * fix typos * fix typo * fix typo * fix typo * fix typos * fix typo * fix typo * fix typo * fix typos * fix typos
This commit is contained in:
@@ -209,7 +209,7 @@ Easily reuse this checkpoint for another task by switching to a different model
|
||||
The last base class you need before using a model for textual data is a [tokenizer](main_classes/tokenizer) to convert raw text to tensors. There are two types of tokenizers you can use with 🤗 Transformers:
|
||||
|
||||
- [`PreTrainedTokenizer`]: a Python implementation of a tokenizer.
|
||||
- [`PreTrainedTokenizerFast`]: a tokenizer from our Rust-based [🤗 Tokenizer](https://huggingface.co/docs/tokenizers/python/latest/) library. This tokenizer type is significantly faster - especially during batch tokenization - due to it's Rust implementation. The fast tokenizer also offers additional methods like *offset mapping* which maps tokens to their original words or characters.
|
||||
- [`PreTrainedTokenizerFast`]: a tokenizer from our Rust-based [🤗 Tokenizer](https://huggingface.co/docs/tokenizers/python/latest/) library. This tokenizer type is significantly faster - especially during batch tokenization - due to its Rust implementation. The fast tokenizer also offers additional methods like *offset mapping* which maps tokens to their original words or characters.
|
||||
|
||||
Both tokenizers support common methods such as encoding and decoding, adding new tokens, and managing special tokens.
|
||||
|
||||
|
||||
Reference in New Issue
Block a user