Practical overview
When it fits
Use it when you want chapter-based, hands-on learning that connects LLM fine-tuning concepts to notebooks, including a route through Google Colab.
Who it is for
- Intermediate learners who want practical instruction in LLM fine-tuning.
- Data scientists and developers seeking to understand quantization, adapters, dataset formatting and training workflows.
Documented uses
- Study 8-bit and 4-bit model quantization and BitsAndBytes configuration.
- Configure LoRA adapters with PEFT and prepare quantized base models for training.
- Format datasets for language-model training using templates, tokenizers and data collators.
- Learn an SFTTrainer fine-tuning workflow and explore local model conversion and serving.
Requirements & limits
The repository is public and MIT-licensed. The README says the Colab notebook route requires a Google Account login and offers Google-provided GPU use.
- The book identifies its level as intermediate and recommends prior familiarity with Transformers, attention, Adam, tokens, embeddings and GPUs.
- The material centers on PyTorch and Hugging Face, with PEFT, BitsAndBytes, SFTTrainer, Colab, Ollama and llama.cpp among the documented topics.
- The README links Kindle, paperback and PDF editions separately from the public notebook repository.
Check current requirements in the official documentation. Source-based guidance does not mean OpenViST has run or independently tested this project.
Open a fine-tuning chapter in Google Colab
Start a repository notebook in Colab and use its documented Google GPU option.
Before you start
- A Google Account login for the Colab route.
Steps
Choose a chapter notebook from the repository README.
Open its linked Colab notebook from GitHub.
Run the notebook using a GPU provided by Google.
Expected outcome
A chapter notebook is open in Colab with the documented option to run it on a Google-provided GPU.
Guide limitations
- This guidance covers opening and selecting the documented runtime option; it does not establish notebook execution results.
Sources & review
Source record details
- Source availability
- Active
- Sources checked
- 15 October 2026
- Original website title
- dvgodoy/FineTuningLLMs · Official homepage title · retained in its source language