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@@ -81,13 +81,13 @@ The programming problems are written in multiple programming languages and conta
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  ## Dataset Structure
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  To lookup currently supported datasets
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  ```python
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- get_dataset_config_names("mxeval/mxeval")
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  ['mathqa-x', 'mbxp', 'multi-humaneval']
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  ```
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  To load a specific dataset and language
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  ```python
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  from datasets import load_dataset
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- load_dataset("mxeval/mxeval", "mbxp", split="python")
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  Dataset({
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  features: ['task_id', 'language', 'prompt', 'test', 'entry_point', 'description', 'canonical_solution'],
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  num_rows: 974
@@ -174,12 +174,12 @@ AWS AI Labs
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  ## Execution
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  ### Execution Example
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- Install the repo [mbxp-exec-eval](https://github.com/amazon-science/mbxp-exec-eval) to execute generations or canonical solutions for the prompts from this dataset.
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  ```python
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  >>> from datasets import load_dataset
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  >>> from mxeval.execution import check_correctness
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- >>> mbxp_python = load_dataset("mxeval/mxeval", "mbxp", split="python")
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  >>> example_problem = mbxp_python[0]
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  >>> check_correctness(example_problem, example_problem["canonical_solution"], timeout=20.0)
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  {'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
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  ### Licensing Information
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- [LICENSE](https://huggingface.co/datasets/mxeval/mxeval/blob/main/LICENSE) <br>
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- [THIRD PARTY LICENSES](https://huggingface.co/datasets/mxeval/mxeval/blob/main/THIRD_PARTY_LICENSES)
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  # Citation Information
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  ```
 
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  ## Dataset Structure
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  To lookup currently supported datasets
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  ```python
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+ get_dataset_config_names("AmazonScience/mxeval")
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  ['mathqa-x', 'mbxp', 'multi-humaneval']
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  ```
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  To load a specific dataset and language
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  ```python
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  from datasets import load_dataset
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+ load_dataset("AmazonScience/mxeval", "mbxp", split="python")
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  Dataset({
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  features: ['task_id', 'language', 'prompt', 'test', 'entry_point', 'description', 'canonical_solution'],
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  num_rows: 974
 
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  ## Execution
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  ### Execution Example
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+ Install the repo [mbxp-exec-eval](https://github.com/amazon-science/mxeval) to execute generations or canonical solutions for the prompts from this dataset.
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  ```python
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  >>> from datasets import load_dataset
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  >>> from mxeval.execution import check_correctness
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+ >>> mbxp_python = load_dataset("AmazonScience/mxeval", "mbxp", split="python")
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  >>> example_problem = mbxp_python[0]
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  >>> check_correctness(example_problem, example_problem["canonical_solution"], timeout=20.0)
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  {'task_id': 'MBPP/1', 'passed': True, 'result': 'passed', 'completion_id': None, 'time_elapsed': 10.582208633422852}
 
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  ### Licensing Information
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+ [LICENSE](https://huggingface.co/datasets/AmazonScience/mxeval/blob/main/LICENSE) <br>
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+ [THIRD PARTY LICENSES](https://huggingface.co/datasets/AmazonScience/mxeval/blob/main/THIRD_PARTY_LICENSES)
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  # Citation Information
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  ```