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Answer: Fine-tune the model on a dataset of image-caption pairs to improve its understanding of the caption generation task.
To generate automated captions for images using an Azure OpenAI model, fine-tuning the model on a dataset of image-caption pairs (C) is the most effective approach. This allows the model to learn the patterns and techniques required for caption generation based on the content of the images. Using a single, broad prompt (A) may not provide enough guidance for the model to generate descriptive captions. Implementing an image recognition system (B) can be helpful but does not directly address the need for training the model on the caption generation task. Limiting the model's captions to a predefined set of keywords or phrases (D) may restrict its ability to generate diverse and relevant captions.
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You are working on a project to generate automated captions for images using an Azure OpenAI model. The model should be able to understand the content of the images and generate descriptive captions. Which of the following techniques should you consider implementing to achieve this?
A
Use a single, broad prompt for all images to maintain consistency in captions.
B
Implement an image recognition system to extract relevant information from the images before generating captions.
C
Fine-tune the model on a dataset of image-caption pairs to improve its understanding of the caption generation task.
D
Limit the model's captions to a predefined set of keywords or phrases.