Use Case Documentation
Finetuned LLM

Choose this use case if you wish to develop a finetuned large language model. Given a dataset containing example prompts and their expected responses, you can fine-tune an LLM that successfully learns to respond as instructed.

Dataset and Feature Group Requirements

This section specifies the Datasets / Feature Groups requirements to successfully train a Finetuned LLM model. Feature requirements include recommendations on additional datasets that might enhance model performance.

Training Models - Training Options and Metrics

This section describes all the available model training options that can be used to create a Finetuned LLM model. You can utilize the metric explanations to better understand how they measure the performance of the model you trained.

Prediction API

This section discusses the prediction API method so that you could properly generate predictions from the model you deployed.

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