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You are working on a project to implement a custom translation model for a specific domain using Azure AI Translator service. The domain has a large amount of technical jargon and specialized vocabulary. Which approach would you take to improve the accuracy of the custom translation model?
A
Use a pre-trained model as the base for the custom model and fine-tune it with a dataset of domain-specific text.
B
Train the custom model from scratch using a large dataset of domain-specific text.
C
Combine multiple pre-trained models and fine-tune them with a dataset of domain-specific text.
D
Use a rule-based approach to handle the technical jargon and specialized vocabulary.