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Kiln - AI Training Tools Tool

Overview

Kiln is an open-source rapid AI prototyping and dataset collaboration tool focused on making model fine-tuning, synthetic data generation, and evaluation accessible to teams. It provides zero-code fine-tuning flows for large language models alongside an open-source Python library to automate and integrate workflows. Kiln targets both individual practitioners and teams by combining desktop apps for Windows, macOS, and Linux with programmatic tooling for reproducible dataset management and model experiments. The platform emphasizes collaboration and iteration: teams can version datasets, generate synthetic examples to augment training sets, run evaluation suites, and iterate on fine-tuning without writing custom training scripts. Kiln’s design lowers the barrier to entry for customizing large language models while retaining advanced controls through its Python SDK. According to the GitHub repository, Kiln has attracted substantial community interest with 4,528 stars and an actively updated codebase (last commit on 2026-01-07), indicating development momentum and real-world usage.

GitHub Statistics

  • Stars: 4,528
  • Forks: 334
  • Contributors: 12
  • License: NOASSERTION
  • Primary Language: Python
  • Last Updated: 2026-01-07T18:59:42Z
  • Latest Release: v0.23.0

According to the GitHub repository, Kiln has 4,528 stars and 334 forks, showing healthy community interest. The project lists 12 contributors and had a recent commit on 2026-01-07, indicating active maintenance. The repository’s license field appears as NOASSERTION on GitHub, so users should verify licensing before production use. The contributor count is modest, suggesting a smaller core team; however, star and fork counts point to a growing user base and adoption among early adopters and researchers.

Installation

Install via pip:

pip install git+https://github.com/Kiln-AI/kiln.git
git clone https://github.com/Kiln-AI/kiln.git && cd kiln && pip install -e .

Key Features

  • Zero-code fine-tuning workflows for large language models, accessible via desktop apps.
  • Synthetic data generation to augment and diversify training datasets.
  • Evaluation suites for automated model comparison and metric tracking.
  • Desktop applications for Windows, macOS, and Linux for local prototyping.
  • Open-source Python library to script, automate, and integrate Kiln workflows.
  • Dataset versioning and team collaboration features to manage shared datasets.

Community

Kiln has an active and growing community, evidenced by 4,528 GitHub stars and 334 forks. The project is actively maintained (last commit 2026-01-07) but has a relatively small contributor base (12), so contributions and issues are likely handled by a compact core team. The repository’s license shows NOASSERTION—community members should confirm license terms before using or redistributing. For up-to-date discussions, issue trackers, and contribution guidelines, consult the project’s GitHub page.

Last Refreshed: 2026-01-09

Key Information

  • Category: Training Tools
  • Type: AI Training Tools Tool
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