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Sebastian Raschka releases an 11-hour video course on building a reasoning model, using…Developments
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Raschka shares an eight-part video course on implementing reasoning models from scratch
Source:Shao Meng
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Oct 26
Shao Meng
Sebastian Raschka releases an 11-hour video course on building a reasoning model, using…
Sebastian Raschka's accompanying video course for "Build a Reasoning Model (From Scratch)" is now available: 11 hours across eight lectures, starting from the pretrained small Qwen3 0.6B and using Python/PyTorch to hand-code a verifier, inference-time scaling (sampling, self-consistency, scoring, self-refinement), a simplified GRPO version of RLVR, and distillation toward a stronger teacher. The course skips training the base model from scratch; the early generation and evaluation work can be done on a CPU, while the later training stages are recommended to use a GPU, with results evaluated on MATH-500. Shao Meng relayed the course design in a tweet and used an engine analogy to distinguish regular LLMs, reasoning models, and the Agent harness.
Oct 25
Ma Dongxi NLP
Dongxi recommends Sebastian Raschka's reasoning model course
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Oct 24
Ahead of AI
Sebastian Raschka releases an 11-hour video course on building a reasoning model from scratch
Sebastian Raschka has released 8 programming videos on building a reasoning model from scratch, totaling 11 hours, using Python and PyTorch to implement evaluation, inference-time scaling, reinforcement learning, and distillation starting from a pretrained Qwen3 0.6B model. The course first builds a math answer verifier and evaluates on MATH-500, then implements temperature sampling, top-p filtering, and self-consistency, followed by RLVR training with a simplified version of GRPO, and finally distills a small model using answers generated by DeepSeek R1. The content accompanies his book "Build a Reasoning Model (From Scratch)"; the early text generation and evaluation examples can run on a CPU, while later training experiments are recommended to use a GPU.
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