Скачать или смотреть Fine-Tune GPT-2 on Custom Data + Resume Training from Checkpoints | Full G

🚀 In this detailed video tutorial, I walk you through the complete process of fine-tuning the GPT-2 language model on a custom dataset and how to continue training from saved checkpoints using the Hugging Face Transformers library.

But that’s not all — I also explain the internal structure of GPT-2 model files, including configuration, tokenizer, and checkpoint files, and how they interact with the Transformers library. This will give you a deep understanding of how the model loads, saves, and resumes training — something most tutorials skip!

✅ What You’ll Learn:

How to prepare and format your own dataset for GPT-2

How to fine-tune GPT-2 using the Hugging Face Transformers library

How to save and load training checkpoints

How to resume training from the last checkpoint

What each GPT-2 model file (like config.json, pytorch_model.bin, tokenizer.json, etc.) means and how Transformers uses them

📁 We’ll explore the following model files in detail:

config.json

tokenizer_config.json

vocab.json and merges.txt

pytorch_model.bin

training_args.bin

Checkpoints and their folder structure

Github - https://github.com/ritikbh193/Fine_tu...
🎯 This tutorial is perfect for anyone building a chatbot, custom text generator, or working on LLM-based applications and wants a solid understanding of GPT-2 fine-tuning with transparency and depth.