metadata

license: mit
task_categories:
  - translation
language:
  - en
tags:
  - code
pretty_name: Base64 decode version1
size_categories:
  - 10K<n<100K
configs:
  - config_name: default
    data_files:
      - split: train
        path: data/data.jsonl

Dataset: Base64 decode version1

This dataset is for improving base64 decoding capabilities.

GPT 4o is great at base64 decoding.

However llama3 is terrible at base64 decoding.

Short examples of what data.jsonl looks like:

{"instruction": "Transform base64 to HEX", "input": "464pNBlIObA=", "output": "e3ae2934194839b0"}
{"instruction": "Decode Base64 to json", "input": "NQ==", "output": "[53]"}
{"instruction": "Base64 to Hexadecimal", "input": "ax0WaQ==", "output": "6b1d1669"}
{"instruction": "convert base64 to Hexadecimal", "input": "8X43", "output": "f17e37"}
{"instruction": "Change base64 to JSON", "input": "7MmBZO4=", "output": "[236,201,129,100,238]"}
{"instruction": "Json from Base64", "input": "ytBBCmPRA6De+Ow=", "output": "[202,208,65,10,99,209,3,160,222,248,236]"}
{"instruction": "BASE64 to Hex", "input": "m/A=", "output": "9bf0"}

Generate dataset

PROMPT> python generate_dataset.py

This creates the data.jsonl file.