instructlab/instructlab

Health v2 · maintenance only

Flags: archived

Adoption not part of the score

1419 stars · 455 forks observed · 2026-08-28

What it is AI-extracted, prompt v1, taxonomy v1, 2026-08-30, confidence not recorded

InstructLab (ilab) is an open-source CLI and Python package for enhancing large language models through community-contributed taxonomy-based skills and knowledge. It uses the LAB alignment method to generate synthetic data from taxonomy contributions and fine-tune base models, supporting local chatting, serving, data generation, and training workflows.

Use cases

• fine-tune an LLM with custom skills and knowledge
• generate synthetic training data from a taxonomy of examples
• chat with a locally served quantized model
• contribute new skills to a community LLM via pull requests
• run the LAB alignment tuning method on a base model
• serve and test a tuned model locally

When to choose

• you want to augment an open LLM with community-contributed skills via synthetic data
• you need an end-to-end local workflow for taxonomy-based tuning, serving, and chatting
• you want to contribute model improvements without retraining from scratch

When to avoid

• you need a fully managed or hosted fine-tuning service
• you only want inference without any model tuning
• you require the newest SDG or training components, which are moving to separate sdg_hub and training_hub repositories

Facets

cli-tool · maturity maintenance

llm-training llm-inference rag data-generation cli chatbot large-language-models artificial-intelligence machine-learning developer-tools python cli llm-alignment synthetic-data taxonomy fine-tuning model-tuning community-contributions linux macos

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For agents

markdown · JSON · MCP: product_card(name="instructlab/instructlab")