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. |