Tuning Engines FAQs

Question 1

What is Tuning Engines and what does it do?

Accepted Answer

Tuning Engines is a platform designed to help you fine-tune open-source Large Language Models (LLMs) and Small Language Models (SLMs) on your custom data. It provides domain-specific models with full control, managed GPU infrastructure, and supports various fine-tuning methods like LoRA and QLoRA.

Question 2

Does Tuning Engines handle the infrastructure for training?

Accepted Answer

Yes, Tuning Engines provides fully managed GPU provisioning, training orchestration, and model delivery. This means you don't need to worry about setting up or maintaining any infrastructure, allowing you to focus purely on your data and model outcomes.

Question 3

How does Tuning Engines create domain-specific AI models?

Accepted Answer

Tuning Engines utilizes specialized training agents to optimize models for particular use cases. For example, Cody specializes in code autocomplete, and SIERA is designed for bug fixing. Future agents will cover customer support, data extraction, security review, and incident response, all trained on your specific data.

Question 4

What types of models can I fine-tune with Tuning Engines?

Accepted Answer

You can fine-tune a wide range of open-source models from 1B to 72B parameters, including popular ones like Qwen, Llama, DeepSeek, Mistral, Gemma, Phi, StarCoder, and CodeLlama. These can be tailored for specific tasks and domains using your proprietary data.

Question 5

How do I interact with Tuning Engines?

Accepted Answer

You can interact with Tuning Engines via its comprehensive Command Line Interface (CLI) for job creation, monitoring, and model management. Additionally, it features an integrated Model Context Protocol (MCP) server, allowing natural language interaction and control through AI assistants like Claude, VS Code, and Cursor.

Tuning Engines

Tuning Engines

Características Principales

Casos de Uso

Características Principales

Casos de Uso