metadata
dataset_info:
features:
- name: question
dtype: string
- name: solutions
dtype: string
- name: starter_code
dtype: string
- name: input_output
dtype: string
- name: difficulty
dtype: string
- name: raw_tags
dtype: string
- name: name
dtype: string
- name: source
dtype: string
- name: tags
dtype: string
- name: skill_types
dtype: string
- name: url
dtype: string
- name: Expected Auxiliary Space
dtype: string
- name: time_limit
dtype: string
- name: date
dtype: string
- name: picture_num
dtype: string
- name: memory_limit
dtype: string
- name: Expected Time Complexity
dtype: string
splits:
- name: train
num_bytes: 4239311973
num_examples: 25443
- name: test
num_bytes: 481480755
num_examples: 1000
download_size: 2419845110
dataset_size: 4720792728
configs:
- config_name: default
data_files:
- split: train
path: data/train-*
- split: test
path: data/test-*
source_datasets: BAAI/TACO
license: apache-2.0
task_categories:
- text-generation
- feature-extraction
language:
- en
tags:
- BAAI/TACO
size_categories:
- 10K<n<100K
BEE-spoke-data/TACO-hf
Simple re-host of https://huggingface.co/datasets/BAAI/TACO but saved as hf dataset for ease of use.
Features:
DatasetDict({
"train": Dataset({
"features": [
"question",
"solutions",
"starter_code",
"input_output",
"difficulty",
"raw_tags",
"name",
"source",
"tags",
"skill_types",
"url",
"Expected Auxiliary Space",
"time_limit",
"date",
"picture_num",
"memory_limit",
"Expected Time Complexity"
],
"num_rows": 25443
}),
"test": Dataset({
"features": [
"question",
"solutions",
"starter_code",
"input_output",
"difficulty",
"raw_tags",
"name",
"source",
"tags",
"skill_types",
"url",
"Expected Auxiliary Space",
"time_limit",
"date",
"picture_num",
"memory_limit",
"Expected Time Complexity"
],
"num_rows": 1000
})
})
Refer to the original dataset for more details.