{"kind":"task","effective_mode":"full","benchmark":{"kind":"benchmark","effective_mode":"full","slug":"bigcodebench","formal_name":"BigCodeBench","introduction":"BigCodeBench poses 1,140 function-level tasks drawn across 139 libraries. It tests whether a model can compose several real APIs correctly rather than write one self-contained function.","introduction_ja":"","introduction_en":"","category":"Category not supplied","task_count":null,"acquisition_status":"Acquisition status not supplied","official_url":"https://bigcode-bench.github.io/","indexing_mode":"index","profile":{"resources":[],"task_format":"","scoring":"","metric":"","size":"","answer_access":"","license":"","citation":"","maintainer":"","released":"","why_hard":"","related":[],"history":"","construction":"","limitations":"","saturation":"","scores":[]}},"task_id":"5d003f49-090c-5eef-8e47-56c7ec4f453e","task_key":"default--v0~2e1~2e0~5fhf--5d003f49-090c-5eef-8e47-56c7ec4f453e","task_revision_id":"1","upstream_id":"","short_description":"BigCodeBench v0.1.0_hf 5d003f49-090c-5eef-8e47-56c7ec4f453e","config":"default","split":"v0.1.0_hf","body":"{\"code_prompt\":\"import re\\nimport nltk\\nnltk.download('stopwords')\\nfrom nltk.corpus import stopwords\\nfrom collections import Counter\\n# Constants\\nSTOPWORDS = set(stopwords.words('english'))\\ndef task_func(text, n=2):\\n\",\"complete_prompt\":\"import re\\nimport nltk\\nnltk.download('stopwords')\\n\\nfrom nltk.corpus import stopwords\\n\\nfrom collections import Counter\\n\\n# Constants\\nSTOPWORDS = set(stopwords.words('english'))\\n\\ndef task_func(text, n=2):\\n    \\\"\\\"\\\"\\n    Remove duplicate and stopwords from a string \\\"text.\\\"\\n    Then, generate a count of n-grams (default is bigrams) in the text.\\n\\n    Parameters:\\n    - text (str): The text string to analyze.\\n    - n (int): The size of the n-grams.\\n\\n    Returns:\\n    - dict: The count of the n-grams in the text.\\n\\n    Requirements:\\n    - re\\n    - nltk.corpus.stopwords\\n    - collections.Counter\\n\\n    Example:\\n    >>> text = \\\"The quick brown fox jumps over the lazy dog and the dog was not that quick to respond.\\\"\\n    >>> ngrams = task_func(text)\\n    >>> print(ngrams)\\n    Counter({('quick', 'brown'): 1, ('brown', 'fox'): 1, ('fox', 'jumps'): 1, ('jumps', 'lazy'): 1, ('lazy', 'dog'): 1, ('dog', 'dog'): 1, ('dog', 'quick'): 1, ('quick', 'respond'): 1})\\n    \\\"\\\"\\\"\\n\",\"entry_point\":\"task_func\",\"instruct_prompt\":\"Remove duplicate and stopwords from a string \\\"text.\\\" Then, generate a count of n-grams (default is bigrams) in the text.\\nThe function should output with:\\n    dict: The count of the n-grams in the text.\\nYou should write self-contained code starting with:\\n```\\nimport re\\nimport nltk\\nnltk.download('stopwords')\\nfrom nltk.corpus import stopwords\\nfrom collections import Counter\\n# Constants\\nSTOPWORDS = set(stopwords.words('english'))\\ndef task_func(text, n=2):\\n```\",\"libs\":\"['nltk', 'collections', 're']\"}","display_format":"code","language":"","answer_status":"published","assets":[],"source_url":"https://bigcode-bench.github.io/","history":"initial import","indexing_mode":"index","subproblems":[],"grids":[]}