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fine-tuning

Fine-tune AI models on 0G's distributed GPU network.

Updated Apr 26, 2026
Search Tags:#cli#ai#fine-tuning#gpu#training#dataset#machine-learning
One-click install
npx skills add https://github.com/gabrielfior/ai-village-open-agents --skill fine-tuning-gabrielfior
Or copy as Structured Prompt for Agent▼
Please help me install this Agent Skill.
Skill: fine-tuning
Source: https://github.com/gabrielfior/ai-village-open-agents/tree/main/.opencode/skills/fine-tuning
Command: npx skills add https://github.com/gabrielfior/ai-village-open-agents --skill fine-tuning-gabrielfior

SYSTEM DOCUMENTATION & REQUIREMENTS

What problem does it solve?

Fine-tune AI models on 0G's distributed GPU network to tailor models to specific tasks.

Core Features & Use Cases

  • Upload training data and configure tuning parameters.
  • Monitor training progress and download the resulting model.
  • Use case: tailor models for domain-specific tasks on the testnet environment.

Quick Start

Upload training data, configure tuning parameters, start the fine-tuning task, and download the resulting model.

Frequently Asked Questions about fine-tuning

High-intent search queries and answers about installing and using this skill.

FAQPage Schema
How do I fine-tune an AI model on a distributed GPU network?▼

To fine-tune an AI model on a distributed GPU network, you must upload your training dataset, configure the tuning parameters, and start the task to monitor progress before downloading the resulting model.

What do I need to run a fine-tuning task on 0G testnet?▼

Running a fine-tuning task on 0G testnet requires Node.js version 22 or higher, the globally installed @0glabs/0g-serving-broker CLI, a testnet wallet funded with 0G tokens, and a formatted training dataset.

How do I configure training parameters for machine-learning models?▼

Configuring training parameters for machine-learning models involves creating a specific configuration file that defines your tuning settings before you upload your training data to the network.

Can I monitor training progress on distributed GPUs remotely?▼

Yes, you can monitor training progress on distributed GPUs remotely through the CLI after your fine-tuning task starts, allowing you to track the machine-learning training cycle until completion.

What format does training data need to be in for AI fine-tuning?▼

AI fine-tuning requires a training dataset in a specific required format to ensure the distributed GPU network can correctly process and tailor the model to your domain-specific tasks.

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