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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I built a tiny LLM to demystify how language models workApr 2026 · github.com · ▲915Built a ~9M param LLM from scratch to understand how they actually work. Vanilla transformer, 60K synthetic conversations, ~130 lines of PyTorch. Trains in 5 min on a free Colab T4. The fish thinks the meaning of life is food. Fork it and swap the personality for your own character.


Fine-tune an 8B model on a 4 GB laptop GPUAug 2026 · github.com · ▲139Fine-tune LLMs from one YAML. Layer streaming trains an 8B model on a 4 GB laptop GPU. - MakazhanAlpamys/Soup

FinetuneDB – AI fine-tuning platform to create custom LLMs2024 · finetunedb.com · ▲152Hey HN! We’re building FinetuneDB (https://finetunedb.com/), an LLM fine-tuning platform. It enables teams to easily create and manage high-quality datasets, and streamlines the entire workflow from fine-tuning to serving and evaluating models with domain experts. You can check out our docs here: (https://docs.finetunedb.com/) FinetuneDB exists because creating and managing high-quality datasets is a real bottleneck when fine-tuning LLMs. The quality of your data directly impacts the performance of your fine-tuned models, and existing tools didn’t offer an easy…
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