|
--- |
|
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: |
|
|
|
```text |
|
{"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. |
