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

MarkTechPost · 2 months ago · 38

The tutorial streams the SupraLabs reasoning-corpus subset from the Hugging Face Hub, analyzes it, filters out examples using token-length, degeneracy, repetition, and reasoning-ratio rules, then converts the result into a chat format with <think> tags for supervised fine-tuning. It trains SmolLM2-135M-Instruct with LoRA (r=16) using 1,500 training samples and evaluates on 100 examples. As a result, it produces a compact reasoning-focused fine-tuned model and exports the curated train/eval subsets to Parquet for reuse in later experiments.