Row 95272

Row ID: 95272 | Dataset Entry | Axioma AXP Content Repository

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Depends on the use case, what tools you have available and what your goals are.

A much bigger model certainly can outperform a finetuned smaller model. Even better is a finetuned big model, but that might not be available to you.

If performance is the only thing that matters to you, then it's best to go as big as possible, and finetune that if possible. However, big models require a lot of costs in GPU usage, so if resources are limited a smaller finetuned model might be the better option.

FieldValue
text Depends on the use case, what tools you have available and what your goals are. A much bigger model certainly can outperform a finetuned smaller model. Even better is a finetuned big model, but that might not be available to you. If performance is the only thing that matters to you, then it's best to go as big as possible, and finetune that if possible. However, big models require a lot of costs in GPU usage, so if resources are limited a smaller finetuned model might be the better option.
label r/machinelearning
dataType comment
communityName r/MachineLearning
datetime 2024-05-25
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Raw Record

{
  "text": "Depends on the use case, what tools you have available and what your goals are.\n\nA much bigger model certainly can outperform a finetuned smaller model. Even better is a finetuned big model, but that might not be available to you.\n\nIf performance is the only thing that matters to you, then it's best to go as big as possible, and finetune that if possible. However, big models require a lot of costs in GPU usage, so if resources are limited a smaller finetuned model might be the better option.",
  "label": "r/machinelearning",
  "dataType": "comment",
  "communityName": "r/MachineLearning",
  "datetime": "2024-05-25",
  "username_encoded": "Z0FBQUFBQm5Lak11dVFZQTRRQklrY2RYMDV6cGVKcGw5cWZoV0x0Ui1jX3lVRGRwQVhvLUM0QkE1MVEydGhYNS02S3VrWkprcUgwQnBfNEJWSERQaVBwdjIwT1dSU2NnNlE9PQ==",
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}
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