Datasets:
Update README.md
Browse files
README.md
CHANGED
|
@@ -81,13 +81,13 @@ The programming problems are written in multiple programming languages and conta
|
|
| 81 |
## Dataset Structure
|
| 82 |
To lookup currently supported datasets
|
| 83 |
```python
|
| 84 |
-
get_dataset_config_names("
|
| 85 |
['mathqa-x', 'mbxp', 'multi-humaneval']
|
| 86 |
```
|
| 87 |
To load a specific dataset and language
|
| 88 |
```python
|
| 89 |
from datasets import load_dataset
|
| 90 |
-
load_dataset("
|
| 91 |
Dataset({
|
| 92 |
features: ['task_id', 'language', 'prompt', 'test', 'entry_point', 'description', 'canonical_solution'],
|
| 93 |
num_rows: 974
|
|
@@ -174,12 +174,12 @@ AWS AI Labs
|
|
| 174 |
## Execution
|
| 175 |
|
| 176 |
### Execution Example
|
| 177 |
-
Install the repo [mbxp-exec-eval](https://github.com/amazon-science/
|
| 178 |
|
| 179 |
```python
|
| 180 |
>>> from datasets import load_dataset
|
| 181 |
>>> from mxeval.execution import check_correctness
|
| 182 |
-
>>> mbxp_python = load_dataset("
|
| 183 |
>>> example_problem = mbxp_python[0]
|
| 184 |
>>> check_correctness(example_problem, example_problem["canonical_solution"], timeout=20.0)
|
| 185 |
{'task_id': 'MBPP/1', 'passed': True, 'result': 'passed', 'completion_id': None, 'time_elapsed': 10.582208633422852}
|
|
@@ -190,8 +190,8 @@ Make sure to sandbox the execution environment since generated code samples can
|
|
| 190 |
|
| 191 |
### Licensing Information
|
| 192 |
|
| 193 |
-
[LICENSE](https://huggingface.co/datasets/
|
| 194 |
-
[THIRD PARTY LICENSES](https://huggingface.co/datasets/
|
| 195 |
|
| 196 |
# Citation Information
|
| 197 |
```
|
|
|
|
| 81 |
## Dataset Structure
|
| 82 |
To lookup currently supported datasets
|
| 83 |
```python
|
| 84 |
+
get_dataset_config_names("AmazonScience/mxeval")
|
| 85 |
['mathqa-x', 'mbxp', 'multi-humaneval']
|
| 86 |
```
|
| 87 |
To load a specific dataset and language
|
| 88 |
```python
|
| 89 |
from datasets import load_dataset
|
| 90 |
+
load_dataset("AmazonScience/mxeval", "mbxp", split="python")
|
| 91 |
Dataset({
|
| 92 |
features: ['task_id', 'language', 'prompt', 'test', 'entry_point', 'description', 'canonical_solution'],
|
| 93 |
num_rows: 974
|
|
|
|
| 174 |
## Execution
|
| 175 |
|
| 176 |
### Execution Example
|
| 177 |
+
Install the repo [mbxp-exec-eval](https://github.com/amazon-science/mxeval) to execute generations or canonical solutions for the prompts from this dataset.
|
| 178 |
|
| 179 |
```python
|
| 180 |
>>> from datasets import load_dataset
|
| 181 |
>>> from mxeval.execution import check_correctness
|
| 182 |
+
>>> mbxp_python = load_dataset("AmazonScience/mxeval", "mbxp", split="python")
|
| 183 |
>>> example_problem = mbxp_python[0]
|
| 184 |
>>> check_correctness(example_problem, example_problem["canonical_solution"], timeout=20.0)
|
| 185 |
{'task_id': 'MBPP/1', 'passed': True, 'result': 'passed', 'completion_id': None, 'time_elapsed': 10.582208633422852}
|
|
|
|
| 190 |
|
| 191 |
### Licensing Information
|
| 192 |
|
| 193 |
+
[LICENSE](https://huggingface.co/datasets/AmazonScience/mxeval/blob/main/LICENSE) <br>
|
| 194 |
+
[THIRD PARTY LICENSES](https://huggingface.co/datasets/AmazonScience/mxeval/blob/main/THIRD_PARTY_LICENSES)
|
| 195 |
|
| 196 |
# Citation Information
|
| 197 |
```
|