What is Post-training?
The refinement stage after a model’s big pre-training — tuning, feedback, and safety work that makes it actually usable.
Post-training is the set of steps applied to a model after pre-training — like fine-tuning and reinforcement learning from human feedback — that shape its behaviour, helpfulness, and safety.
The full picture
Pre-training gives a model broad knowledge, but a raw pre-trained model isn’t ready for real use. Post-training is the refinement phase: techniques like supervised fine-tuning and reinforcement learning from human feedback (RLHF) teach the model to follow instructions, be helpful, stay on-topic, and avoid harmful output.
Post-training is where much of a model’s practical "personality" and safety comes from, and a major reason two models built on similar foundations can feel very different. It’s also more accessible than pre-training — businesses can sometimes apply their own light post-training to adapt a base model to their needs.
📌 Real business example
A company adapts an open-weight base model with light post-training on its own support transcripts, so the assistant answers in the company’s tone and follows its policies.
How different roles use this
Common questions
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