Datasets:
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.
The number of bytes that are in the base64 encoded data spans between 0..127 bytes.
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.