This skill allows agents to fine-tune Large Language Models (LLMs) using Vertex AI's managed tuning service. It encapsulates the workflow for data preparation, job submission, monitoring, and model deployment.

Setup

1. Clone the repo

Add instruction here with the correct repo handle

git clone repo-link

2. Installing Agent Skills

Install the skill to your favorite AI assisted coding tool.

Verification

To confirm the installation was successful ask:

"What skills do you have?"

The agent should respond with a list including your newly added skill vertex-tuning alongside its default capabilities.

Getting started

Try the following prompt to get started:

"I want to fine-tune a Llama 3.1 8B model for text classification on Vertex. Can you help me with this?"

Features

Data Preparation: Converts and validates datasets (JSONL format) for Vertex AI.
Model Tuning: Submits tuning jobs for supported models (Llama, Gemma, Qwen, etc.) with customizable hyperparameters (PEFT/Full).
Model Deployment: Deploys tuned models to Vertex AI Endpoints for serving.
Guidance: Provides recommendations for models and hyperparameters based on the task and dataset.

Directory Structure

scripts/: Python scripts for each stage of the workflow.
- prepare_dataset.py: Converts, splits, and validates datasets.
- tune_model.py: Submits the tuning job to Vertex AI.
- deploy_model.py: Deploys the tuned model to an endpoint.
references/: Documentation and catalogs.
- models.md: Supported models, hardware requirements, and hyperparameter baselines.
- data_prep.md: Data formatting guidelines.
- tuning_guide.md: Detailed tuning advice.