Sagify - Train and deploy ML/DL models on AWS SageMaker made simple
LLMs and Machine Learning done easily. Contribute to Kenza-AI/sagify development by creating an account on GitHub.
Sagify - Train and deploy ML/DL models on AWS SageMaker made simple launched on May 8, 2018 with 5 votes and more than 50% of that year's launches. The site was still online in September 2026, 8 years on.
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Amazon SageMaker2017 · aws.amazon.com · ▲10Build, train, and deploy machine learning models at scale

TuneTrain.ai2025 · tunetrain.ai · ▲79Do 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…

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