OpenAI announces upgrades to its fine-tuning API, offering developers enhanced control over the model training process. Alongside these improvements, the company is expanding its custom models program…
This guide explains model distillation: using a large teacher model's outputs (e.g., GPT-4o) to train a smaller, cheaper student model via OpenAI's built-in workflow. It covers when distillation makes…
OpenAI has extended fine-tuning for GPT-4o to support both images and text, allowing developers to train the model on custom visual data for tasks like product recognition, defect inspection, and docu…
RAG updates context at query time; fine-tuning updates model behavior. Choose RAG for changing facts and fine-tuning for consistent output.
Recent research demonstrates that language models can be effectively guided toward specific behavioral values by fine-tuning on a small, carefully curated dataset. This approach highlights the power o…
This article investigates how exposing language models to incorrect answers during training can cause misalignment to generalize into broader alignment failures. The researchers identify a specific in…
This tutorial shows developers how to improve schema compliance in small local language models by fine-tuning LiquidAI's LFM2.5-350M using GRPO with TRL and LoRA. Using ~500 Nemotron structured-output…
