Fine-tune machine learning models on Azure AI Foundry with Python scripts.
npx skills add https://github.com/jorgeasaurus/agent-skills --skill finetuning-jorgeasaurus
Please help me install this Agent Skill. Skill: finetuning Source: https://github.com/jorgeasaurus/agent-skills/tree/main/finetuning Command: npx skills add https://github.com/jorgeasaurus/agent-skills --skill finetuning-jorgeasaurus
This Skill streamlines the process of fine-tuning machine learning models, enabling users to quickly adjust models to their specific needs using supervised fine-tuning, preference-based fine-tuning, or reinforcement learning with graders.
Run the following command to start the fine-tuning process for your model: python scripts/submit_training.py --model your-model-id --training-file train-data.jsonl --validation-file validation-data.jsonl --type sft
High-intent search queries and answers about installing and using this skill.
Fine-tuning a machine learning model with supervised learning requires preparing labeled data, submitting a training job via Python scripts, and evaluating the deployed model's performance using Azure AI Foundry services.
Supervised fine-tuning customizes models using labeled data, preference-based fine-tuning optimizes based on human preferences, and reinforcement fine-tuning trains models through interaction with external tools or feedback from graders.
Yes, model training jobs require Azure AI Foundry because the process utilizes Azure services and dependencies like azure-identity and azure-ai-projects to submit training jobs, deploy models, and evaluate performance.
You start a fine-tuning job by running the submit_training.py Python script with arguments specifying your model ID, training data file, validation data file, and the fine-tuning type like sft for supervised learning.
Model training and validation support JSONL data formats, requiring you to provide a training file and a validation file, such as train-data.jsonl and validation-data.jsonl, to prepare data for the supervised fine-tuning process.
Model fine-tuning requires the openai library version 1.0 or higher, azure-identity, and azure-ai-projects Python dependencies to interact with Azure AI Foundry services for training, deployment, and evaluation.
anishi1222Fine-tune AI models on Azure AI Foundry with supervised, preference, or reinforcement learning.
ScientiaCapitalExport fine-tuned models to GGUF and deploy with vLLM or Ollama.
Avihai-HDeploy, evaluate, and troubleshoot Foundry agents and models in Azure AI Foundry.
pmcdowallDeploy and manage ML workloads on serverless GPU infrastructure.
