LLMs-from-scratch/ch07/02_dataset-utilities
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Co-authored-by: Sebastian Raschka <mail@sebastianraschka.com>
2024-07-16 07:07:04 -05:00
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Chapter 7: Finetuning to Follow Instructions

This folder contains utility code that can be used for preparing an instruction dataset.

Install the additional package requirements via:

pip install -r requirements-extra.txt

Finding Near Duplicates

The find-near-duplicates.py function can be used to identify duplicates and near-duplicates in an instruction dataset. For example,

python find-near-duplicates.py --json_file instruction-examples.json
scikit-learn version: 1.3.1


==================================================
Searching 'instruction' for duplicates ...
==================================================
Duplicate pair found with similarity 0.94:
1. Edit the following sentence to make it more formal.
2. Edit the sentence to make it more formal.

Duplicate pair found with similarity 1.00:
1. Name a dwarf planet in our solar system.
2. Name a dwarf planet in our solar system.

Duplicate pair found with similarity 0.91:
1. Change the sentences from active voice to passive voice.
2. Change the sentence from passive to active voice.



==================================================
Searching 'input' for duplicates ...
==================================================
No duplicates found


==================================================
Searching 'output' for duplicates ...
==================================================
Duplicate pair found with similarity 1.00:
1. One dwarf planet in our solar system is Pluto.
2. One dwarf planet in our solar system is Pluto.


  You can use the --threshold setting with a value between 0 and 1 to decrease or increase the sensitivity. The default threshold is 0.9.

 

Creating Passive Voice Entries

{  
   'instruction': 'Identify the verb in the following sentence',
   'input': 'The cat sleeps on the couch.',
   'output': 'The verb in the sentence is "sleeps."',
   'output_2': 'The sentence is "sleeps."'   #  <---- Newly created entry
}