Update README.md

README.md

@@ -1,3 +1,97 @@
+---
+license: apache-2.0
+pretty_name: HumanEvalPack
+language:
+- code
+---
+# Dataset Card for CommitPackFT
 
+## Table of Contents
+- [Table of Contents](#table-of-contents)
+- [Dataset Description](#dataset-description)
+  - [Dataset Summary](#dataset-summary)
+  - [Languages](#languages)
+- [Dataset Structure](#dataset-structure)
+  - [Data Instances](#data-instances)
+  - [Data Fields](#data-fields)
+  - [Data Splits](#data-splits)
+- [Dataset Creation](#dataset-creation)
+  - [Curation Rationale](#curation-rationale)
+  - [Source Data](#source-data)
+  - [Annotations](#annotations)
+- [Additional Information](#additional-information)
+  - [Licensing Information](#licensing-information)
+  - [Citation Information](#citation-information)
+  - [Contributions](#contributions)
 
-WIP
+## Dataset Description
+
+- **Repository:** https://github.com/bigcode-project/octopack
+- **Paper:** WIP
+- **Point of Contact:** [Niklas Muennighoff](mailto:n.muennighoff@gmail.com)
+
+### Dataset Summary
+
+> HumanEvalPack is ...
+> 
+- **Languages:** 6
+- **OctoPack:**
+- 
+
+## Dataset Structure
+
+
+### Data Instances
+
+
+An example looks as follows:
+
+```json
+{
+  "task_id": "Python/0",
+  "prompt": "from typing import List\n\n\ndef has_close_elements(numbers: List[float], threshold: float) -> bool:\n    \"\"\" Check if in given list of numbers, are any two numbers closer to each other than\n    given threshold.\n    >>> has_close_elements([1.0, 2.0, 3.0], 0.5)\n    False\n    >>> has_close_elements([1.0, 2.8, 3.0, 4.0, 5.0, 2.0], 0.3)\n    True\n    \"\"\"\n",
+  "canonical_solution": "    for idx, elem in enumerate(numbers):\n        for idx2, elem2 in enumerate(numbers):\n            if idx != idx2:\n                distance = abs(elem - elem2)\n                if distance < threshold:\n                    return True\n\n    return False\n",
+  "test": "\n\n\n\n\ndef check(has_close_elements):\n    assert has_close_elements([1.0, 2.0, 3.9, 4.0, 5.0, 2.2], 0.3) == True\n    assert has_close_elements([1.0, 2.0, 3.9, 4.0, 5.0, 2.2], 0.05) == False\n    assert has_close_elements([1.0, 2.0, 5.9, 4.0, 5.0], 0.95) == True\n    assert has_close_elements([1.0, 2.0, 5.9, 4.0, 5.0], 0.8) == False\n    assert has_close_elements([1.0, 2.0, 3.0, 4.0, 5.0, 2.0], 0.1) == True\n    assert has_close_elements([1.1, 2.2, 3.1, 4.1, 5.1], 1.0) == True\n    assert has_close_elements([1.1, 2.2, 3.1, 4.1, 5.1], 0.5) == False\n\ncheck(has_close_elements)",
+  "text": "    Check if in given list of numbers, are any two numbers closer to each other than\n    given threshold.\n    >>> has_close_elements([1.0, 2.0, 3.0], 0.5)\n    False\n    >>> has_close_elements([1.0, 2.8, 3.0, 4.0, 5.0, 2.0], 0.3)\n    True",
+  "declaration": "from typing import List\n\n\ndef has_close_elements(numbers: List[float], threshold: float) -> bool:\n",
+  "example_test": "def check(has_close_elements):\n    assert has_close_elements([1.0, 2.0, 3.0], 0.5) == False\n    assert has_close_elements([1.0, 2.8, 3.0, 4.0, 5.0, 2.0], 0.3) == True\ncheck(has_close_elements)\n",
+  "buggy_solution": "    for idx, elem in enumerate(numbers):\n        for idx2, elem2 in enumerate(numbers):\n            if idx != idx2:\n                distance = elem - elem2\n                if distance < threshold:\n                    return True\n\n    return False\n",
+  "bug_type": "missing logic",
+  "failure_symptoms": "incorrect output",
+  "entry_point": "has_close_elements",
+  "signature": "has_close_elements(numbers: List[float], threshold: float) -> bool",
+  "docstring": "Check if in given list of numbers, are any two numbers closer to each other than\ngiven threshold.\n>>> has_close_elements([1.0, 2.0, 3.0], 0.5)\nFalse\n>>> has_close_elements([1.0, 2.8, 3.0, 4.0, 5.0, 2.0], 0.3)\nTrue",
+  "instruction": "Write a Python function `has_close_elements(numbers: List[float], threshold: float) -> bool` to solve the following problem:\nCheck if in given list of numbers, are any two numbers closer to each other than\ngiven threshold.\n>>> has_close_elements([1.0, 2.0, 3.0], 0.5)\nFalse\n>>> has_close_elements([1.0, 2.8, 3.0, 4.0, 5.0, 2.0], 0.3)\nTrue"
+}
+```
+
+### Data Fields
+
+The data fields are the same among all splits:
+- `task_id`: task id (from 0 to 163)
+- `prompt`: the prompt for models relying on code continuation
+- `canonical_solution`: the correct solution passing all unit tests for the problem
+- `test`: the unit tests for the problem
+- `text`: ???
+- `declaration`: the declaration of the function (same as prompt but without the docstring)
+- `example_test`: ??? Same as test but fewer tests
+- `buggy_solution`: same as `canonical_solution` but with a subtle human-written bug causing the unit tests to fail
+- `bug_type`: the type of the bug in `buggy_solution` (one of [`missing logic`, `excess logic`, `value misuse`, `operator misuse`, `variable misuse`, `function misuse`])
+- `failure_symptoms`: the problem the bug causes (one of [`incorrect output`, `stackoverflow`, `infinite loop`])
+- `entry_point`: the name of the function
+- `signature`: the signature of the function
+- `docstring`: the docstring describing the problem
+- `instruction`: an instruction for HumanEvalSynthesize in the form `Write a {language_name} function {signature} to solve the following problem:\n{docstring}`
+
+### Data Splits
+
+## Additional Information
+
+### Licensing Information
+
+Each sample has comes from a code repository with a permissive license. The license is provided by the `license` field for each sample.
+
+### Citation Information
+
+```bibtex
+```