Fine-tuning adapts a pre-trained model to a specific task or style by training it further on a smaller, labeled dataset. It trades some generality for better fit.
In practice, Fine-tuning shows up across many AI tools. Below are 8 tools where the idea is useful - open any to see it applied.
Developer console and API keys for the Claude model family
Node-based local interface for running image and video diffusion models
Browser playground for prompting and prototyping with Gemini models
Hosted Jupyter notebooks with optional free GPU and TPU runtimes
Where most of the open machine learning world lives
Datasets, competitions and hosted notebooks for machine learning
Open-source framework for building applications on language models
Runs open-weight language models locally behind a local API