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AI · October 9, 2025

TuneTrain.ai

Do you know that Small Language Models (SLM) can outperform LLMs if trained (fine-tuned) on domain specific datasets, like your companies knowledge base? The issue: fine-tuning a SLM usually requires a dataset of 10k - 100k records, which is huge. I created a platform for applying "human in the loop" augmentation techniques on your small dataset, so that you can start with maybe 100 records and build-up quickly huge datasets and launch a training without prior knowledge. I implemented 2 techniques, based on LLM distillation, however: more to come. HN, what Do you think? Do you see value in…

TuneTrain.ai launched on October 9, 2025 with 79 votes, #357 of 8,178 launches that month and more than 90% of that year's launches. The site was still online in September 2026, 1 year on.

What it does

TuneTrain.ai - Fine-tune AI models with your data TuneTrain.ai lets anyone fine-tune small language models easily - no coding or huge datasets needed. Create example records, augment them into large datasets, and train your own custom AI.

Fine-tune language models with your data

Transform your data into powerful, customized language models. Augment your dataset, select a model, and deploy your fine-tuned AI easily. Fine-tune from a curated selection of state-of-the-art small language models, optimized for efficiency and performance. Professional AI model fine-tuning made simple and accessible for businesses of all sizes. Easily upload, organize, and manage your datasets in CSV and JSONL formats. Track versions and maintain data quality. Generate synthetic data variations and expand your datasets automatically to improve model performance and diversity. Leverage large language models to distill knowledge into smaller, efficient models while maintaining quality.…from tunetrain.ai

In the maker’s words, at launch

Do you know that Small Language Models (SLM) can outperform LLMs if trained (fine-tuned) on domain specific datasets, like your companies knowledge base? The issue: fine-tuning a SLM usually requires a dataset of 10k - 100k records, which is huge. I created a platform for applying "human in the loop" augmentation…

Does a similar job

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