
# Raw Data from MultiPL-E

**Uploads are a work in progress. If you are interested in a split that is not yet available, please contact a.guha@northeastern.edu.**

This repository contains the raw data -- both completions and executions -- from MultiPL-E that was used to generate several experimental results from the 
MultiPL-E, SantaCoder, and StarCoder papers.

The original MultiPL-E completions and executions are stored in JOSN files. We use [the following script](https://github.com/nuprl/MultiPL-E/blob/main/upload_completions.py-)
to turn each experiment directory into a dataset split and upload to this repository.

Every split is named `base_dataset`.`language`.`model`.`temperature`.`variation`

- `base_dataset` is either `humaneval` or `mbpp`.
- `language` is the file extension of the programming language. E.g., `py` for Python or `sh` for Bash.
- `model` is the name of the model. Some model names used by MultiPL-E:
   - `bigcode_15b_1000m`:  StarCoderBase
   - `bigcode_15b_200m`, `bigcode_15b_400m`, `bigcode_15b_600m`, `bigcode_15b_800m`: the 20%, 40%, 60%, 80% checkpoints for StarCoderBase
  - `pystarcoder2`: StarCoder
   - there are others, just have a look :)
- `temperature`: this is either 0.2 or 0.8
- `variation`: the variation of the MultiPL-E prompt to use, which should be `reworded`. MultiPL-E has several prompt ablations and the `reworded` prompts are the canonical variation.
code region:us
{"pretty_name": "MultiPL-E generated programs and execution results", "dataset_info": {"features": [{"name": "experiment", "dtype": "string"}, {"name": "problem", "dtype": "string"}, {"name": "language", "dtype": "string"}, {"name": "top_p", "dtype": "float64"}, {"name": "max_tokens", "dtype": "int64"}, {"name": "prompt", "dtype": "string"}, {"name": "tests", "dtype": "string"}, {"name": "stop_tokens", "sequence": "string"}, {"name": "completions", "sequence": "string"}, {"name": "programs", "sequence": "string"}, {"name": "stdouts", "sequence": "string"}, {"name": "stderrs", "sequence": "string"}, {"name": "exit_codes", "sequence": "int64"}, {"name": "statuses", "sequence": "string"}, {"name": "timestamps", "sequence": "int64"}], "splits": [{"name": "humaneval.py.bigcode_15b_800m.0.2.reworded", "num_bytes": 50941974, "num_examples": 161}, {"name": "humaneval.py.bigcode_15b_200m.0.2.reworded", "num_bytes": 57850786, "num_examples": 161}, {"name": 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TAGS
#code #region-us 


# Raw Data from MultiPL-E

Uploads are a work in progress. If you are interested in a split that is not yet available, please contact a.guha@URL.

This repository contains the raw data -- both completions and executions -- from MultiPL-E that was used to generate several experimental results from the 
MultiPL-E, SantaCoder, and StarCoder papers.

The original MultiPL-E completions and executions are stored in JOSN files. We use the following script
to turn each experiment directory into a dataset split and upload to this repository.

Every split is named 'base_dataset'.'language'.'model'.'temperature'.'variation'

- 'base_dataset' is either 'humaneval' or 'mbpp'.
- 'language' is the file extension of the programming language. E.g., 'py' for Python or 'sh' for Bash.
- 'model' is the name of the model. Some model names used by MultiPL-E:
   - 'bigcode_15b_1000m':  StarCoderBase
   - 'bigcode_15b_200m', 'bigcode_15b_400m', 'bigcode_15b_600m', 'bigcode_15b_800m': the 20%, 40%, 60%, 80% checkpoints for StarCoderBase
  - 'pystarcoder2': StarCoder
   - there are others, just have a look :)
- 'temperature': this is either 0.2 or 0.8
- 'variation': the variation of the MultiPL-E prompt to use, which should be 'reworded'. MultiPL-E has several prompt ablations and the 'reworded' prompts are the canonical variation.
# Raw Data from MultiPL-E

Uploads are a work in progress. If you are interested in a split that is not yet available, please contact a.guha@URL.

This repository contains the raw data -- both completions and executions -- from MultiPL-E that was used to generate several experimental results from the 
MultiPL-E, SantaCoder, and StarCoder papers.

The original MultiPL-E completions and executions are stored in JOSN files. We use the following script
to turn each experiment directory into a dataset split and upload to this repository.

Every split is named 'base_dataset'.'language'.'model'.'temperature'.'variation'

- 'base_dataset' is either 'humaneval' or 'mbpp'.
- 'language' is the file extension of the programming language. E.g., 'py' for Python or 'sh' for Bash.
- 'model' is the name of the model. Some model names used by MultiPL-E:
   - 'bigcode_15b_1000m':  StarCoderBase
   - 'bigcode_15b_200m', 'bigcode_15b_400m', 'bigcode_15b_600m', 'bigcode_15b_800m': the 20%, 40%, 60%, 80% checkpoints for StarCoderBase
  - 'pystarcoder2': StarCoder
   - there are others, just have a look :)
- 'temperature': this is either 0.2 or 0.8
- 'variation': the variation of the MultiPL-E prompt to use, which should be 'reworded'. MultiPL-E has several prompt ablations and the 'reworded' prompts are the canonical variation.
TAGS
#code #region-us 
 # Raw Data from MultiPL-E

Uploads are a work in progress. If you are interested in a split that is not yet available, please contact a.guha@URL.

This repository contains the raw data -- both completions and executions -- from MultiPL-E that was used to generate several experimental results from the 
MultiPL-E, SantaCoder, and StarCoder papers.

The original MultiPL-E completions and executions are stored in JOSN files. We use the following script
to turn each experiment directory into a dataset split and upload to this repository.

Every split is named 'base_dataset'.'language'.'model'.'temperature'.'variation'

- 'base_dataset' is either 'humaneval' or 'mbpp'.
- 'language' is the file extension of the programming language. E.g., 'py' for Python or 'sh' for Bash.
- 'model' is the name of the model. Some model names used by MultiPL-E:
   - 'bigcode_15b_1000m':  StarCoderBase
   - 'bigcode_15b_200m', 'bigcode_15b_400m', 'bigcode_15b_600m', 'bigcode_15b_800m': the 20%, 40%, 60%, 80% checkpoints for StarCoderBase
  - 'pystarcoder2': StarCoder
   - there are others, just have a look :)
- 'temperature': this is either 0.2 or 0.8
- 'variation': the variation of the MultiPL-E prompt to use, which should be 'reworded'. MultiPL-E has several prompt ablations and the 'reworded' prompts are the canonical variation.
passage: TAGS
#code #region-us 
# Raw Data from MultiPL-E

Uploads are a work in progress. If you are interested in a split that is not yet available, please contact a.guha@URL.

This repository contains the raw data -- both completions and executions -- from MultiPL-E that was used to generate several experimental results from the 
MultiPL-E, SantaCoder, and StarCoder papers.

The original MultiPL-E completions and executions are stored in JOSN files. We use the following script
to turn each experiment directory into a dataset split and upload to this repository.

Every split is named 'base_dataset'.'language'.'model'.'temperature'.'variation'

- 'base_dataset' is either 'humaneval' or 'mbpp'.
- 'language' is the file extension of the programming language. E.g., 'py' for Python or 'sh' for Bash.
- 'model' is the name of the model. Some model names used by MultiPL-E:
   - 'bigcode_15b_1000m':  StarCoderBase
   - 'bigcode_15b_200m', 'bigcode_15b_400m', 'bigcode_15b_600m', 'bigcode_15b_800m': the 20%, 40%, 60%, 80% checkpoints for StarCoderBase
  - 'pystarcoder2': StarCoder
   - there are others, just have a look :)
- 'temperature': this is either 0.2 or 0.8
- 'variation': the variation of the MultiPL-E prompt to use, which should be 'reworded'. MultiPL-E has several prompt ablations and the 'reworded' prompts are the canonical variation.