I’ve been exploring various AI and ML models, and I keep coming across the terms ‘completion input’ and ‘task input.’ I understand that they are used in different contexts, but I’m curious to learn more about their specific differences, use cases, and best practices.
What are the main differences between ‘completion input’ and ‘task input’?
Why are these distinctions important in AI/ML models?
What are the pros and cons of using ‘completion input’ versus ‘task input’?
Can you share any best practical tips for working with both types of inputs?
Looking forward to hearing your insights and experiences!
In the context of language models, completion input means querying a model to complete the given input like sentences, paragraph, stories. The task input is used for specifying a particular tasks like questioning, summary, classify, translate, analyze for the given text. Here is the gist for two kind of inputs.
The completion input is useful when querying the model about the pretrained knowledge but the task input plays a role to finetune the model based on the requirements.
The task input has more flexible, precise and might be complex compared to completion input.
Please follow the document to practice and experiment the models with these kind of inputs.
Thank You