h2oai/h2o-llmstudio

Health v2 · maintenance only

Adoption not part of the score

5172 stars · 555 forks observed · 2026-08-28

What it is AI-extracted, prompt v1, taxonomy v1, 2026-08-29, confidence not recorded

H2O LLM Studio is a framework and no-code GUI for fine-tuning state-of-the-art large language models, built by H2O.ai. It supports LoRA and 8-bit low-memory training, RL-based fine-tuning, experiment tracking with W&B, model chat evaluation, and export to the Hugging Face Hub.

Use cases

• fine-tune an LLM on custom instruction data without writing code
• apply LoRA or 8-bit training to fit large models on limited GPU memory
• compare and track fine-tuning experiments visually
• chat with a fine-tuned model to evaluate its answers
• export a fine-tuned model to the Hugging Face Hub
• run fine-tuning jobs from the command line or CI

When to choose

• you want a GUI-driven, no-code workflow for LLM fine-tuning
• you need low-memory techniques like LoRA and 8-bit training
• you want built-in experiment tracking, evaluation, and chat testing
• you plan to publish models to the Hugging Face Hub

When to avoid

• you need fully programmatic, scriptable training pipelines with custom training loops
• you are not working with LLMs (e.g., vision or tabular models)
• you lack GPU resources for training
• you need a lightweight library to embed in an existing ML stack rather than a standalone studio

Facets

framework · maturity active

llm-training machine-learning gui cli gpu-computing large-language-models machine-learning deep-learning artificial-intelligence python cross-platform fine-tuning lora no-code huggingface reinforcement-learning wave-gui wandb docker linux gpu

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markdown · JSON · MCP: product_card(name="h2oai/h2o-llmstudio")