examples/hello-train/README.md
This example demonstrates how to define a training interface in Cog using the train: field in cog.yaml.
The training API allows you to define a fine-tuning interface for an existing Cog model, so users of the model can bring their own training data to create derivative fine-tuned models. Real-world examples of this API in use include fine-tuning SDXL with images or fine-tuning Llama 2 with structured text.
This simple trainable model takes a string as input and returns a string as output.
Note: The cog train CLI command is deprecated. Training is still supported via the Replicate API and the train: field in cog.yaml.
Run predictions with:
cog predict -i text=world