Datasets:
Tasks:
Translation
Modalities:
Text
Formats:
json
Languages:
English
Size:
10K - 100K
Tags:
code
License:
license: mit | |
task_categories: | |
- translation | |
language: | |
- en | |
tags: | |
- code | |
pretty_name: Base64 encode version1 | |
size_categories: | |
- 10K<n<100K | |
configs: | |
- config_name: default | |
data_files: | |
- split: train | |
path: data/data.jsonl | |
# Dataset: Base64 encode version1 | |
This dataset is for improving base64 encoding capabilities. | |
`GPT 4o` is great at base64 encoding. | |
``` | |
user: | |
convert this hex data to base64: | |
880567a1 | |
assistant: | |
The base64 encoding of the hex data `880567a1` is `iAVnoQ==`. | |
user: | |
convert this json data representing a byte sequence to base64: | |
[30,41,183] | |
assistant: | |
The base64 encoding of the JSON data `[30,41,183]` is `Him3`. | |
``` | |
However `llama3` is terrible at base64 encoding. | |
Short examples of what `data.jsonl` looks like: | |
```text | |
{"instruction": "Encode hex to Base64", "input": "ecfc2db9ba6049165b", "output": "7PwtubpgSRZb"} | |
{"instruction": "change HEX to base64", "input": "60926e782008", "output": "YJJueCAI"} | |
{"instruction": "Json to base64", "input": "[77,62,160,64,248,233,105,133,5,248,89,239]", "output": "TT6gQPjpaYUF+Fnv"} | |
{"instruction": "Change Json to BASE64", "input": "[10,59,42,251,112,1]", "output": "Cjsq+3AB"} | |
{"instruction": "Convert JSON to Base64", "input": "[236,201,129,100,238]", "output": "7MmBZO4="} | |
``` | |
# Generate dataset | |
``` | |
PROMPT> python generate_dataset.py | |
``` | |
This creates the `data.jsonl` file. |