colab-finetuning

What problem does it solve?

This Skill addresses the challenge of fine-tuning large language models on Google Colab, providing efficient and scalable parameter-efficient fine-tuning (PEFT) methods.

Core Features & Use Cases

• Advanced PEFT Methods: Offers LoRA, QLoRA, DPO, ORPO, and PPO methods for fine-tuning.
• Multi-GPU Support: Allows fine-tuning on multiple GPUs for increased speed and capacity.
• Gradient Checkpointing: Implements gradient checkpointing for efficient memory usage.
• Dataset Strategies: Provides guidance on dataset preparation for PEFT.
• Evaluation: Offers evaluation methods for fine-tuned models.
• Export Formats: Supports various export formats for fine-tuned models.
• Use Case: Ideal for researchers and developers looking to fine-tune large language models on Colab with minimal VRAM and time.

Quick Start

Run the following command to fine-tune a model using QLoRA on Colab:

!pip install "unsloth[colab-new] @ git+https://github.com/unslothai/unsloth.git"
!pip install peft trl bitsandbytes gradio -q