ashishpatel26/LLM-Finetuning resource

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2980 stars · 771 forks observed · 2026-08-28

What it is AI-extracted, prompt v1, taxonomy v1, 2026-08-30, confidence not recorded

A collection of Jupyter/Colab notebooks demonstrating efficient fine-tuning of large language models (Llama 2, Falcon, Guanaco) using LoRA and Hugging Face's PEFT library. It serves as a hands-on tutorial resource for parameter-efficient LLM training.

Use cases

• learn how to fine-tune llama 2 with lora
• peft fine-tuning tutorial notebooks
• train a custom chatbot from llama 7b
• run llm fine-tuning in google colab
• parameter-efficient fine-tuning examples with huggingface
• fine-tune falcon or guanaco models

When to choose

• you want runnable Colab notebooks for LoRA/PEFT fine-tuning
• you're learning LLM fine-tuning on consumer or free-tier GPUs
• you need examples for Llama 2, Falcon, or Guanaco models

When to avoid

• you need a production training pipeline or library rather than notebooks
• you require a maintained, licensed software package
• you need full fine-tuning rather than parameter-efficient methods

Facets

learning-resource · maturity active

llm-training machine-learning deep-learning large-language-models machine-learning deep-learning tutorials python cross-platform peft lora huggingface llama2 falcon jupyter-notebooks colab fine-tuning text-generation gpu

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