Fine-Tune LLM on Text Summarization task from scratch | Pytorch | Python
In this video, we dive deep into the world of Large Language Models (LLMs) by learning how to fine-tune one from scratch on a text summarization task! We will be using the TinyStories 19 Million parameter base model and fine-tuning it on the TinyStories instruct dataset for summarizing stories.
We will walk through the initial base model and how it generates tiny stories. We will further train that model on summarization tasks. The lecture involves dataset preparation and fine-tuning from scratch with the Pytorch framework. We will also understand how to shift the model parameters and training dataset on GPU for speeding up the training process.
Access the Notebook: https://github.com/SauravP97/llm-fine...
Github Repo: https://github.com/SauravP97/llm-fine...
Fine-tuned TinyStories 19M model: https://huggingface.co/SauravP97/tiny...
TinyStories Paper: https://arxiv.org/pdf/2305.07759
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