A step-by-step guide on automating the execution of Jupyter Notebooks and generating HTML reports using Python scripts. The article explains how Jupyter Notebooks can be used for creating interactive reports and how their execution can be synchronized with data pipelines to update reports automatically.
Jupyter notebook for using LlamaIndex with arXiv papers for retrieval-augmented generation (RAG).
This GitHub repository contains information on fine-tuning large language models (LLMs).
It includes a Jupyter Notebook file named "7 Steps to Fine-Tune LLMs.ipynb" that outlines the process.
Users can find information on setting up the environment, preparing data, fine-tuning models, evaluating performance, and saving fine-tuned models.
It includes a Jupyter Notebook file named "7 Steps to Fine-Tune LLMs.ipynb" that outlines the process.
Users can find information on setting up the environment, preparing data, fine-tuning models, evaluating performance, and saving fine-tuned models.
