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A user gets gibberish output from a text generation model. What is a likely error in their code?

medium📝 Debug Q7 of 15
NLP - Text Generation
A user gets gibberish output from a text generation model. What is a likely error in their code?
AThey used a very large max_length value
BThey did not preprocess the input text correctly before generation
CThey set the temperature parameter to zero
DThey used a pretrained model
Step-by-Step Solution
Solution:

  1. Step 1: Understand gibberish cause

    Incorrect input preprocessing can cause the model to generate nonsensical text.

  2. Step 2: Rule out other options

    Large max_length or zero temperature usually affect length or randomness, not gibberish alone.

  3. Final Answer:

    They did not preprocess the input text correctly before generation -> Option B

  4. Quick Check:

    Proper preprocessing = meaningful output [OK]
Quick Trick: Always preprocess input text correctly [OK]
Common Mistakes:
MISTAKES
  • Ignoring input preprocessing
  • Blaming max_length for gibberish
  • Assuming pretrained models cause gibberish

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