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[demo]: Inferring Multiple choice Questions #337

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appledora opened this issue Mar 11, 2024 · 0 comments
Open
3 tasks done

[demo]: Inferring Multiple choice Questions #337

appledora opened this issue Mar 11, 2024 · 0 comments

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@appledora
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appledora commented Mar 11, 2024

Before you open an issue, please check if a similar issue already exists or has been closed before.

When you open an issue, please be sure to include the following

  • A descriptive title: [xxx] XXXX
  • A detailed description
  • Assign an issue type tag (label):
    • dataset (mimic-it download, usage, etc.),
    • demo (online demo), doc (readme, wiki, paper, video etc.),
    • evaluation (evaluation result, performance of Otter etc.),
    • model (model configuration, components, etc.),
    • train (training configuration, process, code, etc.)

Thank you for your contributions!

Hello, I am trying to use the in-context model (luodian/OTTER-9B-LA-InContext) to generate output from a multiple-choice question. My primary instruction looks something like this:

prompt = "<image>User: Can you pick one of the following options that best describes the image? Choose ONLY from the given two options. <options>1: cat 2: dog GPT:<answer> 1: cat<|endofchunk|><image>User: Can you pick one of the following options that best describes the image? Choose ONLY from the given two options.  <options>1: kitchen table 2: bathroom sink GPT:<answer> 2: bathroom sink<|endofchunk|><image>User: Can you pick one of the following options that best describes the image? Choose ONLY from the given two options. <options>1: chicken_wings 2: salad GPT:<answer> " 

However, considering the outputs, I feel like I am not structuring this correctly or not using the correct model for this task. I am looking for suggestions to improve my instruction, and whether I should try the different weights.

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