this post was submitted on 21 Nov 2023
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LocalLLaMA

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Community to discuss about Llama, the family of large language models created by Meta AI.

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I'm thinking of using Llama 2 to detect spam messages:

  1. The model will first be fine tuned using LoRa/PEFT with some public dataset.

  2. Then, when given a block of text, it will decide if it's spam and provide reasons for the user.

  3. However, there can be false positives etc., so I figured a way to combat this would be to let the user tell the model if the response is correct or wrong (thumbs up/down).

Based on my requirements, is it better to use RLHF or DPO? Am I over complicating this, will fine tuning it based on user feedback work too?

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[–] oKatanaa@alien.top 1 points 10 months ago

You're better off using something like BERT rather than shooting a pigeon with a ballistic missile. It easier, cheaper, faster and much more reliable.