LLM Tokenizers, from HFs LNP Course
Failed to add items
Sorry, we are unable to add the item because your shopping basket is already at capacity.
Add to cart failed.
Please try again later
Add to wishlist failed.
Please try again later
Remove from wishlist failed.
Please try again later
Follow podcast failed
Unfollow podcast failed
-
Narrated by:
-
Written by:
About this listen
This excerpt from Hugging Face's NLP course provides a comprehensive overview of tokenization techniques used in natural language processing. Tokenizers are essential tools for transforming raw text into numerical data that machine learning models can understand. The text explores various tokenization methods, including word-based, character-based, and subword tokenization, highlighting their advantages and disadvantages. It then focuses on the encoding process, where text is first split into tokens and then converted to input IDs. Finally, the text demonstrates how to decode input IDs back into human-readable text.
Read more: https://huggingface.co/learn/nlp-course/en/chapter2/4
No reviews yet