L-10 | How to Train a Tokenizer on Your Own Dataset for LLMs скачать в хорошем качестве

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. Subscribe for more practical AI tutorials 🚀 📸 Follow me on Instagram: @codewithaarohihindi 🔗   / codewithaarohihindi   📧 You can also reach me at: aarohisingla1987@gmail.com