References:
full
Use the following command to load this dataset in TFDS:
ds = tfds.load('huggingface:mbpp/full')
- Description:
The MBPP (Mostly Basic Python Problems) dataset consists of around 1,000 crowd-sourced Python
programming problems, designed to be solvable by entry level programmers, covering programming
fundamentals, standard library functionality, and so on. Each problem consists of a task
description, code solution and 3 automated test cases.
- License: CC-BY-4.0
- Version: 1.0.0
- Splits:
| Split | Examples |
|---|---|
'test' |
974 |
- Features:
{
"task_id": {
"dtype": "int32",
"id": null,
"_type": "Value"
},
"text": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"code": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"test_list": {
"feature": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"length": -1,
"id": null,
"_type": "Sequence"
},
"test_setup_code": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"challenge_test_list": {
"feature": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"length": -1,
"id": null,
"_type": "Sequence"
}
}
sanitized
Use the following command to load this dataset in TFDS:
ds = tfds.load('huggingface:mbpp/sanitized')
- Description:
The MBPP (Mostly Basic Python Problems) dataset consists of around 1,000 crowd-sourced Python
programming problems, designed to be solvable by entry level programmers, covering programming
fundamentals, standard library functionality, and so on. Each problem consists of a task
description, code solution and 3 automated test cases.
- License: CC-BY-4.0
- Version: 1.0.0
- Splits:
| Split | Examples |
|---|---|
'test' |
427 |
- Features:
{
"source_file": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"task_id": {
"dtype": "int32",
"id": null,
"_type": "Value"
},
"prompt": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"code": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"test_imports": {
"feature": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"length": -1,
"id": null,
"_type": "Sequence"
},
"test_list": {
"feature": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"length": -1,
"id": null,
"_type": "Sequence"
}
}