How can we improve tokenization in NLP?

How can we improve tokenization in NLP?

Improving tokenization can involve using more advanced algorithms, like subword tokenization, to handle rare words better.

What are some common tokenization techniques?

Common techniques include whitespace tokenization, punctuation-based tokenization, and subword tokenization like Byte Pair Encoding.

How does subword tokenization work?

Subword tokenization breaks words into smaller units, allowing the model to understand and generate rare or unseen words.

Can tokenization affect model performance?

Yes, poor tokenization can lead to loss of meaning and context, negatively impacting the model's performance.

What tools can I use for tokenization?

You can use libraries like NLTK, SpaCy, or Hugging Face's Tokenizers for effective tokenization in NLP tasks.