Meta’s ‘open’ AI, and a $250M deal gone very wrong

Create a Reasoning-Focused LLM: A Practical Guide to Streaming, Curating, and Fine-Tuning the SupraLabs Reasoning Corpus

In this tutorial, we build an end-to-end workflow for working with the SupraLabs reasoning corpus. We stream a representative subset directly from the Hugging Face Hub, inspect its source distribution, token-length patterns, task composition, and reasoning-to-answer ratios, and then apply a series of quality filters to remove unsuitable training examples. We transform the retained samples into a chat-based supervised fine-tuning format with explicit <think> reasoning tags and use them to ada