Скачать или смотреть L-10 | How to Train a Tokenizer on Your Own Dataset for LLMs

In this video, we learn how to train a tokenizer on a domain-specific dataset step by step. Instead of using a general-purpose tokenizer, we create a custom tokenizer tailored to our own data.

GitHub: https://github.com/codewithaarohi/Tra...

We cover:

What a tokenizer is and why it matters in NLP

Why domain-specific tokenization improves model performance

How subword tokenization (BPE) works

Training a tokenizer using the Hugging Face tokenizers library

Generating a custom vocabulary file

Real examples of domain-specific tokenization

If you're working on LLMs, NLP projects, or fine-tuning models on custom data, training your own tokenizer can significantly improve results.

Perfect for:
AI engineers, NLP learners, LLM enthusiasts, and anyone building domain-specific language models.

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