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H2O LLM Studio

A no-code GUI framework for fine-tuning Large Language Models, with an intuitive dashboard and experiment tracking

★ 5,045 GitHub Apache-2.0 llmfine-tuningno-codeguihuggingfacetransformersdeep-learning LLM & Chat

Overview

H2O LLM Studio is a powerful open-source framework that provides a no-code graphical interface for fine-tuning large language models (LLMs). It offers an intuitive dashboard where you can manage datasets, configure training parameters, track experiments, and evaluate model performance - all without writing a single line of code. Built on top of Hugging Face Transformers, it supports a wide range of pre-trained models and comes with built-in experiment tracking, hyperparameter optimization, and GPU acceleration.

Requirements

Min vCPU
2
Min RAM
4096 MB
Min Disk
10 GB
Rec vCPU
4
Rec RAM
8192 MB
Rec Disk
20 GB

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Affiliate disclosure

Docker Compose

# Generated by Run This Ai — docker-compose.yml
services:
  h2o-llmstudio:
    image: glavin001/h2o-llmstudio:latest
    restart: unless-stopped
    ports:
      - 8080:8080
    volumes:
      - ./data/h2o-llmstudio:/data

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Guides & articles

H2O LLM Studio Review: No-Code LLM Fine-Tuning Made Easy

An honest hands-on review of H2O LLM Studio. Performance benchmarks, strengths, limitations, and whether it is right for your LLM fine-tuning workflow.

Jul 28, 2026

How to Fine-Tune LLMs with H2O LLM Studio: A Complete Guide

Learn how to fine-tune large language models using H2O LLM Studio's no-code interface. Step-by-step guide covering datasets, training, and deployment.

Jul 28, 2026