conjunto de dados_matemático

Referências:

álgebra__linear_1d

Use o seguinte comando para carregar este conjunto de dados no TFDS:

ds = tfds.load('huggingface:math_dataset/algebra__linear_1d')
  • Descrição :
Mathematics database.

This dataset code generates mathematical question and answer pairs,
from a range of question types at roughly school-level difficulty.
This is designed to test the mathematical learning and algebraic
reasoning skills of learning models.

Original paper: Analysing Mathematical Reasoning Abilities of Neural Models
(Saxton, Grefenstette, Hill, Kohli).

Example usage:
train_examples, val_examples = datasets.load_dataset(
    'math_dataset/arithmetic__mul',
    split=['train', 'test'],
    as_supervised=True)
  • Licença : Nenhuma licença conhecida
  • Versão : 1.0.0
  • Divisões :
Dividir Exemplos
'test' 10.000
'train' 1999998
  • Características : 
{
    "question": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "answer": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    }
}

álgebra__linear_1d_composto

Use o seguinte comando para carregar este conjunto de dados no TFDS:

ds = tfds.load('huggingface:math_dataset/algebra__linear_1d_composed')
  • Descrição :
Mathematics database.

This dataset code generates mathematical question and answer pairs,
from a range of question types at roughly school-level difficulty.
This is designed to test the mathematical learning and algebraic
reasoning skills of learning models.

Original paper: Analysing Mathematical Reasoning Abilities of Neural Models
(Saxton, Grefenstette, Hill, Kohli).

Example usage:
train_examples, val_examples = datasets.load_dataset(
    'math_dataset/arithmetic__mul',
    split=['train', 'test'],
    as_supervised=True)
  • Licença : Nenhuma licença conhecida
  • Versão : 1.0.0
  • Divisões :
Dividir Exemplos
'test' 10.000
'train' 1999998
  • Características : 
{
    "question": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "answer": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    }
}

álgebra__linear_2d

Use o seguinte comando para carregar este conjunto de dados no TFDS:

ds = tfds.load('huggingface:math_dataset/algebra__linear_2d')
  • Descrição :
Mathematics database.

This dataset code generates mathematical question and answer pairs,
from a range of question types at roughly school-level difficulty.
This is designed to test the mathematical learning and algebraic
reasoning skills of learning models.

Original paper: Analysing Mathematical Reasoning Abilities of Neural Models
(Saxton, Grefenstette, Hill, Kohli).

Example usage:
train_examples, val_examples = datasets.load_dataset(
    'math_dataset/arithmetic__mul',
    split=['train', 'test'],
    as_supervised=True)
  • Licença : Nenhuma licença conhecida
  • Versão : 1.0.0
  • Divisões :
Dividir Exemplos
'test' 10.000
'train' 1999998
  • Características : 
{
    "question": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "answer": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    }
}

álgebra__linear_2d_composto

Use o seguinte comando para carregar este conjunto de dados no TFDS:

ds = tfds.load('huggingface:math_dataset/algebra__linear_2d_composed')
  • Descrição :
Mathematics database.

This dataset code generates mathematical question and answer pairs,
from a range of question types at roughly school-level difficulty.
This is designed to test the mathematical learning and algebraic
reasoning skills of learning models.

Original paper: Analysing Mathematical Reasoning Abilities of Neural Models
(Saxton, Grefenstette, Hill, Kohli).

Example usage:
train_examples, val_examples = datasets.load_dataset(
    'math_dataset/arithmetic__mul',
    split=['train', 'test'],
    as_supervised=True)
  • Licença : Nenhuma licença conhecida
  • Versão : 1.0.0
  • Divisões :
Dividir Exemplos
'test' 10.000
'train' 1999998
  • Características : 
{
    "question": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "answer": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    }
}

álgebra__polynomial_roots

Use o seguinte comando para carregar este conjunto de dados no TFDS:

ds = tfds.load('huggingface:math_dataset/algebra__polynomial_roots')
  • Descrição :
Mathematics database.

This dataset code generates mathematical question and answer pairs,
from a range of question types at roughly school-level difficulty.
This is designed to test the mathematical learning and algebraic
reasoning skills of learning models.

Original paper: Analysing Mathematical Reasoning Abilities of Neural Models
(Saxton, Grefenstette, Hill, Kohli).

Example usage:
train_examples, val_examples = datasets.load_dataset(
    'math_dataset/arithmetic__mul',
    split=['train', 'test'],
    as_supervised=True)
  • Licença : Nenhuma licença conhecida
  • Versão : 1.0.0
  • Divisões :
Dividir Exemplos
'test' 10.000
'train' 1999998
  • Características : 
{
    "question": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "answer": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    }
}

álgebra__polinomial_roots_composto

Use o seguinte comando para carregar este conjunto de dados no TFDS:

ds = tfds.load('huggingface:math_dataset/algebra__polynomial_roots_composed')
  • Descrição :
Mathematics database.

This dataset code generates mathematical question and answer pairs,
from a range of question types at roughly school-level difficulty.
This is designed to test the mathematical learning and algebraic
reasoning skills of learning models.

Original paper: Analysing Mathematical Reasoning Abilities of Neural Models
(Saxton, Grefenstette, Hill, Kohli).

Example usage:
train_examples, val_examples = datasets.load_dataset(
    'math_dataset/arithmetic__mul',
    split=['train', 'test'],
    as_supervised=True)
  • Licença : Nenhuma licença conhecida
  • Versão : 1.0.0
  • Divisões :
Dividir Exemplos
'test' 10.000
'train' 1999998
  • Características : 
{
    "question": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "answer": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    }
}

álgebra__sequence_next_term

Use o seguinte comando para carregar este conjunto de dados no TFDS:

ds = tfds.load('huggingface:math_dataset/algebra__sequence_next_term')
  • Descrição :
Mathematics database.

This dataset code generates mathematical question and answer pairs,
from a range of question types at roughly school-level difficulty.
This is designed to test the mathematical learning and algebraic
reasoning skills of learning models.

Original paper: Analysing Mathematical Reasoning Abilities of Neural Models
(Saxton, Grefenstette, Hill, Kohli).

Example usage:
train_examples, val_examples = datasets.load_dataset(
    'math_dataset/arithmetic__mul',
    split=['train', 'test'],
    as_supervised=True)
  • Licença : Nenhuma licença conhecida
  • Versão : 1.0.0
  • Divisões :
Dividir Exemplos
'test' 10.000
'train' 1999998
  • Características : 
{
    "question": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "answer": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    }
}

álgebra__sequence_nth_term

Use o seguinte comando para carregar este conjunto de dados no TFDS:

ds = tfds.load('huggingface:math_dataset/algebra__sequence_nth_term')
  • Descrição :
Mathematics database.

This dataset code generates mathematical question and answer pairs,
from a range of question types at roughly school-level difficulty.
This is designed to test the mathematical learning and algebraic
reasoning skills of learning models.

Original paper: Analysing Mathematical Reasoning Abilities of Neural Models
(Saxton, Grefenstette, Hill, Kohli).

Example usage:
train_examples, val_examples = datasets.load_dataset(
    'math_dataset/arithmetic__mul',
    split=['train', 'test'],
    as_supervised=True)
  • Licença : Nenhuma licença conhecida
  • Versão : 1.0.0
  • Divisões :
Dividir Exemplos
'test' 10.000
'train' 1999998
  • Características : 
{
    "question": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "answer": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    }
}

aritmética__adicionar_ou_sub

Use o seguinte comando para carregar este conjunto de dados no TFDS:

ds = tfds.load('huggingface:math_dataset/arithmetic__add_or_sub')
  • Descrição :
Mathematics database.

This dataset code generates mathematical question and answer pairs,
from a range of question types at roughly school-level difficulty.
This is designed to test the mathematical learning and algebraic
reasoning skills of learning models.

Original paper: Analysing Mathematical Reasoning Abilities of Neural Models
(Saxton, Grefenstette, Hill, Kohli).

Example usage:
train_examples, val_examples = datasets.load_dataset(
    'math_dataset/arithmetic__mul',
    split=['train', 'test'],
    as_supervised=True)
  • Licença : Nenhuma licença conhecida
  • Versão : 1.0.0
  • Divisões :
Dividir Exemplos
'test' 10.000
'train' 1999998
  • Características : 
{
    "question": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "answer": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    }
}

aritmética__add_or_sub_in_base

Use o seguinte comando para carregar este conjunto de dados no TFDS:

ds = tfds.load('huggingface:math_dataset/arithmetic__add_or_sub_in_base')
  • Descrição :
Mathematics database.

This dataset code generates mathematical question and answer pairs,
from a range of question types at roughly school-level difficulty.
This is designed to test the mathematical learning and algebraic
reasoning skills of learning models.

Original paper: Analysing Mathematical Reasoning Abilities of Neural Models
(Saxton, Grefenstette, Hill, Kohli).

Example usage:
train_examples, val_examples = datasets.load_dataset(
    'math_dataset/arithmetic__mul',
    split=['train', 'test'],
    as_supervised=True)
  • Licença : Nenhuma licença conhecida
  • Versão : 1.0.0
  • Divisões :
Dividir Exemplos
'test' 10.000
'train' 1999998
  • Características : 
{
    "question": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "answer": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    }
}

aritmética__add_sub_multiple

Use o seguinte comando para carregar este conjunto de dados no TFDS:

ds = tfds.load('huggingface:math_dataset/arithmetic__add_sub_multiple')
  • Descrição :
Mathematics database.

This dataset code generates mathematical question and answer pairs,
from a range of question types at roughly school-level difficulty.
This is designed to test the mathematical learning and algebraic
reasoning skills of learning models.

Original paper: Analysing Mathematical Reasoning Abilities of Neural Models
(Saxton, Grefenstette, Hill, Kohli).

Example usage:
train_examples, val_examples = datasets.load_dataset(
    'math_dataset/arithmetic__mul',
    split=['train', 'test'],
    as_supervised=True)
  • Licença : Nenhuma licença conhecida
  • Versão : 1.0.0
  • Divisões :
Dividir Exemplos
'test' 10.000
'train' 1999998
  • Características : 
{
    "question": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "answer": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    }
}

aritmética__div

Use o seguinte comando para carregar este conjunto de dados no TFDS:

ds = tfds.load('huggingface:math_dataset/arithmetic__div')
  • Descrição :
Mathematics database.

This dataset code generates mathematical question and answer pairs,
from a range of question types at roughly school-level difficulty.
This is designed to test the mathematical learning and algebraic
reasoning skills of learning models.

Original paper: Analysing Mathematical Reasoning Abilities of Neural Models
(Saxton, Grefenstette, Hill, Kohli).

Example usage:
train_examples, val_examples = datasets.load_dataset(
    'math_dataset/arithmetic__mul',
    split=['train', 'test'],
    as_supervised=True)
  • Licença : Nenhuma licença conhecida
  • Versão : 1.0.0
  • Divisões :
Dividir Exemplos
'test' 10.000
'train' 1999998
  • Características : 
{
    "question": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "answer": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    }
}

aritmética__mista

Use o seguinte comando para carregar este conjunto de dados no TFDS:

ds = tfds.load('huggingface:math_dataset/arithmetic__mixed')
  • Descrição :
Mathematics database.

This dataset code generates mathematical question and answer pairs,
from a range of question types at roughly school-level difficulty.
This is designed to test the mathematical learning and algebraic
reasoning skills of learning models.

Original paper: Analysing Mathematical Reasoning Abilities of Neural Models
(Saxton, Grefenstette, Hill, Kohli).

Example usage:
train_examples, val_examples = datasets.load_dataset(
    'math_dataset/arithmetic__mul',
    split=['train', 'test'],
    as_supervised=True)
  • Licença : Nenhuma licença conhecida
  • Versão : 1.0.0
  • Divisões :
Dividir Exemplos
'test' 10.000
'train' 1999998
  • Características : 
{
    "question": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "answer": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    }
}

aritmética__mul

Use o seguinte comando para carregar este conjunto de dados no TFDS:

ds = tfds.load('huggingface:math_dataset/arithmetic__mul')
  • Descrição :
Mathematics database.

This dataset code generates mathematical question and answer pairs,
from a range of question types at roughly school-level difficulty.
This is designed to test the mathematical learning and algebraic
reasoning skills of learning models.

Original paper: Analysing Mathematical Reasoning Abilities of Neural Models
(Saxton, Grefenstette, Hill, Kohli).

Example usage:
train_examples, val_examples = datasets.load_dataset(
    'math_dataset/arithmetic__mul',
    split=['train', 'test'],
    as_supervised=True)
  • Licença : Nenhuma licença conhecida
  • Versão : 1.0.0
  • Divisões :
Dividir Exemplos
'test' 10.000
'train' 1999998
  • Características : 
{
    "question": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "answer": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    }
}

aritmética__mul_div_multiple

Use o seguinte comando para carregar este conjunto de dados no TFDS:

ds = tfds.load('huggingface:math_dataset/arithmetic__mul_div_multiple')
  • Descrição :
Mathematics database.

This dataset code generates mathematical question and answer pairs,
from a range of question types at roughly school-level difficulty.
This is designed to test the mathematical learning and algebraic
reasoning skills of learning models.

Original paper: Analysing Mathematical Reasoning Abilities of Neural Models
(Saxton, Grefenstette, Hill, Kohli).

Example usage:
train_examples, val_examples = datasets.load_dataset(
    'math_dataset/arithmetic__mul',
    split=['train', 'test'],
    as_supervised=True)
  • Licença : Nenhuma licença conhecida
  • Versão : 1.0.0
  • Divisões :
Dividir Exemplos
'test' 10.000
'train' 1999998
  • Características : 
{
    "question": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "answer": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    }
}

arithmetic__nearest_integer_root

Use o seguinte comando para carregar este conjunto de dados no TFDS:

ds = tfds.load('huggingface:math_dataset/arithmetic__nearest_integer_root')
  • Descrição :
Mathematics database.

This dataset code generates mathematical question and answer pairs,
from a range of question types at roughly school-level difficulty.
This is designed to test the mathematical learning and algebraic
reasoning skills of learning models.

Original paper: Analysing Mathematical Reasoning Abilities of Neural Models
(Saxton, Grefenstette, Hill, Kohli).

Example usage:
train_examples, val_examples = datasets.load_dataset(
    'math_dataset/arithmetic__mul',
    split=['train', 'test'],
    as_supervised=True)
  • Licença : Nenhuma licença conhecida
  • Versão : 1.0.0
  • Divisões :
Dividir Exemplos
'test' 10.000
'train' 1999998
  • Características : 
{
    "question": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "answer": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    }
}

aritmética__simplify_surd

Use o seguinte comando para carregar este conjunto de dados no TFDS:

ds = tfds.load('huggingface:math_dataset/arithmetic__simplify_surd')
  • Descrição :
Mathematics database.

This dataset code generates mathematical question and answer pairs,
from a range of question types at roughly school-level difficulty.
This is designed to test the mathematical learning and algebraic
reasoning skills of learning models.

Original paper: Analysing Mathematical Reasoning Abilities of Neural Models
(Saxton, Grefenstette, Hill, Kohli).

Example usage:
train_examples, val_examples = datasets.load_dataset(
    'math_dataset/arithmetic__mul',
    split=['train', 'test'],
    as_supervised=True)
  • Licença : Nenhuma licença conhecida
  • Versão : 1.0.0
  • Divisões :
Dividir Exemplos
'test' 10.000
'train' 1999998
  • Características : 
{
    "question": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "answer": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    }
}

cálculo__diferenciar

Use o seguinte comando para carregar este conjunto de dados no TFDS:

ds = tfds.load('huggingface:math_dataset/calculus__differentiate')
  • Descrição :
Mathematics database.

This dataset code generates mathematical question and answer pairs,
from a range of question types at roughly school-level difficulty.
This is designed to test the mathematical learning and algebraic
reasoning skills of learning models.

Original paper: Analysing Mathematical Reasoning Abilities of Neural Models
(Saxton, Grefenstette, Hill, Kohli).

Example usage:
train_examples, val_examples = datasets.load_dataset(
    'math_dataset/arithmetic__mul',
    split=['train', 'test'],
    as_supervised=True)
  • Licença : Nenhuma licença conhecida
  • Versão : 1.0.0
  • Divisões :
Dividir Exemplos
'test' 10.000
'train' 1999998
  • Características : 
{
    "question": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "answer": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    }
}

cálculo__diferenciar_composto

Use o seguinte comando para carregar este conjunto de dados no TFDS:

ds = tfds.load('huggingface:math_dataset/calculus__differentiate_composed')
  • Descrição :
Mathematics database.

This dataset code generates mathematical question and answer pairs,
from a range of question types at roughly school-level difficulty.
This is designed to test the mathematical learning and algebraic
reasoning skills of learning models.

Original paper: Analysing Mathematical Reasoning Abilities of Neural Models
(Saxton, Grefenstette, Hill, Kohli).

Example usage:
train_examples, val_examples = datasets.load_dataset(
    'math_dataset/arithmetic__mul',
    split=['train', 'test'],
    as_supervised=True)
  • Licença : Nenhuma licença conhecida
  • Versão : 1.0.0
  • Divisões :
Dividir Exemplos
'test' 10.000
'train' 1999998
  • Características : 
{
    "question": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "answer": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    }
}

comparação__mais próximo

Use o seguinte comando para carregar este conjunto de dados no TFDS:

ds = tfds.load('huggingface:math_dataset/comparison__closest')
  • Descrição :
Mathematics database.

This dataset code generates mathematical question and answer pairs,
from a range of question types at roughly school-level difficulty.
This is designed to test the mathematical learning and algebraic
reasoning skills of learning models.

Original paper: Analysing Mathematical Reasoning Abilities of Neural Models
(Saxton, Grefenstette, Hill, Kohli).

Example usage:
train_examples, val_examples = datasets.load_dataset(
    'math_dataset/arithmetic__mul',
    split=['train', 'test'],
    as_supervised=True)
  • Licença : Nenhuma licença conhecida
  • Versão : 1.0.0
  • Divisões :
Dividir Exemplos
'test' 10.000
'train' 1999998
  • Características : 
{
    "question": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "answer": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    }
}

comparação__mais próximo_composto

Use o seguinte comando para carregar este conjunto de dados no TFDS:

ds = tfds.load('huggingface:math_dataset/comparison__closest_composed')
  • Descrição :
Mathematics database.

This dataset code generates mathematical question and answer pairs,
from a range of question types at roughly school-level difficulty.
This is designed to test the mathematical learning and algebraic
reasoning skills of learning models.

Original paper: Analysing Mathematical Reasoning Abilities of Neural Models
(Saxton, Grefenstette, Hill, Kohli).

Example usage:
train_examples, val_examples = datasets.load_dataset(
    'math_dataset/arithmetic__mul',
    split=['train', 'test'],
    as_supervised=True)
  • Licença : Nenhuma licença conhecida
  • Versão : 1.0.0
  • Divisões :
Dividir Exemplos
'test' 10.000
'train' 1999998
  • Características : 
{
    "question": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "answer": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    }
}

comparação__kth_biggest

Use o seguinte comando para carregar este conjunto de dados no TFDS:

ds = tfds.load('huggingface:math_dataset/comparison__kth_biggest')
  • Descrição :
Mathematics database.

This dataset code generates mathematical question and answer pairs,
from a range of question types at roughly school-level difficulty.
This is designed to test the mathematical learning and algebraic
reasoning skills of learning models.

Original paper: Analysing Mathematical Reasoning Abilities of Neural Models
(Saxton, Grefenstette, Hill, Kohli).

Example usage:
train_examples, val_examples = datasets.load_dataset(
    'math_dataset/arithmetic__mul',
    split=['train', 'test'],
    as_supervised=True)
  • Licença : Nenhuma licença conhecida
  • Versão : 1.0.0
  • Divisões :
Dividir Exemplos
'test' 10.000
'train' 1999998
  • Características : 
{
    "question": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "answer": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    }
}

comparação__kth_biggest_composed

Use o seguinte comando para carregar este conjunto de dados no TFDS:

ds = tfds.load('huggingface:math_dataset/comparison__kth_biggest_composed')
  • Descrição :
Mathematics database.

This dataset code generates mathematical question and answer pairs,
from a range of question types at roughly school-level difficulty.
This is designed to test the mathematical learning and algebraic
reasoning skills of learning models.

Original paper: Analysing Mathematical Reasoning Abilities of Neural Models
(Saxton, Grefenstette, Hill, Kohli).

Example usage:
train_examples, val_examples = datasets.load_dataset(
    'math_dataset/arithmetic__mul',
    split=['train', 'test'],
    as_supervised=True)
  • Licença : Nenhuma licença conhecida
  • Versão : 1.0.0
  • Divisões :
Dividir Exemplos
'test' 10.000
'train' 1999998
  • Características : 
{
    "question": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "answer": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    }
}

comparação__par

Use o seguinte comando para carregar este conjunto de dados no TFDS:

ds = tfds.load('huggingface:math_dataset/comparison__pair')
  • Descrição :
Mathematics database.

This dataset code generates mathematical question and answer pairs,
from a range of question types at roughly school-level difficulty.
This is designed to test the mathematical learning and algebraic
reasoning skills of learning models.

Original paper: Analysing Mathematical Reasoning Abilities of Neural Models
(Saxton, Grefenstette, Hill, Kohli).

Example usage:
train_examples, val_examples = datasets.load_dataset(
    'math_dataset/arithmetic__mul',
    split=['train', 'test'],
    as_supervised=True)
  • Licença : Nenhuma licença conhecida
  • Versão : 1.0.0
  • Divisões :
Dividir Exemplos
'test' 10.000
'train' 1999998
  • Características : 
{
    "question": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "answer": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    }
}

comparação__par_composto

Use o seguinte comando para carregar este conjunto de dados no TFDS:

ds = tfds.load('huggingface:math_dataset/comparison__pair_composed')
  • Descrição :
Mathematics database.

This dataset code generates mathematical question and answer pairs,
from a range of question types at roughly school-level difficulty.
This is designed to test the mathematical learning and algebraic
reasoning skills of learning models.

Original paper: Analysing Mathematical Reasoning Abilities of Neural Models
(Saxton, Grefenstette, Hill, Kohli).

Example usage:
train_examples, val_examples = datasets.load_dataset(
    'math_dataset/arithmetic__mul',
    split=['train', 'test'],
    as_supervised=True)
  • Licença : Nenhuma licença conhecida
  • Versão : 1.0.0
  • Divisões :
Dividir Exemplos
'test' 10.000
'train' 1999998
  • Características : 
{
    "question": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "answer": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    }
}

comparação__sort

Use o seguinte comando para carregar este conjunto de dados no TFDS:

ds = tfds.load('huggingface:math_dataset/comparison__sort')
  • Descrição :
Mathematics database.

This dataset code generates mathematical question and answer pairs,
from a range of question types at roughly school-level difficulty.
This is designed to test the mathematical learning and algebraic
reasoning skills of learning models.

Original paper: Analysing Mathematical Reasoning Abilities of Neural Models
(Saxton, Grefenstette, Hill, Kohli).

Example usage:
train_examples, val_examples = datasets.load_dataset(
    'math_dataset/arithmetic__mul',
    split=['train', 'test'],
    as_supervised=True)
  • Licença : Nenhuma licença conhecida
  • Versão : 1.0.0
  • Divisões :
Dividir Exemplos
'test' 10.000
'train' 1999998
  • Características : 
{
    "question": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "answer": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    }
}

comparação__sort_composed

Use o seguinte comando para carregar este conjunto de dados no TFDS:

ds = tfds.load('huggingface:math_dataset/comparison__sort_composed')
  • Descrição :
Mathematics database.

This dataset code generates mathematical question and answer pairs,
from a range of question types at roughly school-level difficulty.
This is designed to test the mathematical learning and algebraic
reasoning skills of learning models.

Original paper: Analysing Mathematical Reasoning Abilities of Neural Models
(Saxton, Grefenstette, Hill, Kohli).

Example usage:
train_examples, val_examples = datasets.load_dataset(
    'math_dataset/arithmetic__mul',
    split=['train', 'test'],
    as_supervised=True)
  • Licença : Nenhuma licença conhecida
  • Versão : 1.0.0
  • Divisões :
Dividir Exemplos
'test' 10.000
'train' 1999998
  • Características : 
{
    "question": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "answer": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    }
}

medição__conversão

Use o seguinte comando para carregar este conjunto de dados no TFDS:

ds = tfds.load('huggingface:math_dataset/measurement__conversion')
  • Descrição :
Mathematics database.

This dataset code generates mathematical question and answer pairs,
from a range of question types at roughly school-level difficulty.
This is designed to test the mathematical learning and algebraic
reasoning skills of learning models.

Original paper: Analysing Mathematical Reasoning Abilities of Neural Models
(Saxton, Grefenstette, Hill, Kohli).

Example usage:
train_examples, val_examples = datasets.load_dataset(
    'math_dataset/arithmetic__mul',
    split=['train', 'test'],
    as_supervised=True)
  • Licença : Nenhuma licença conhecida
  • Versão : 1.0.0
  • Divisões :
Dividir Exemplos
'test' 10.000
'train' 1999998
  • Características : 
{
    "question": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "answer": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    }
}

medição__tempo

Use o seguinte comando para carregar este conjunto de dados no TFDS:

ds = tfds.load('huggingface:math_dataset/measurement__time')
  • Descrição :
Mathematics database.

This dataset code generates mathematical question and answer pairs,
from a range of question types at roughly school-level difficulty.
This is designed to test the mathematical learning and algebraic
reasoning skills of learning models.

Original paper: Analysing Mathematical Reasoning Abilities of Neural Models
(Saxton, Grefenstette, Hill, Kohli).

Example usage:
train_examples, val_examples = datasets.load_dataset(
    'math_dataset/arithmetic__mul',
    split=['train', 'test'],
    as_supervised=True)
  • Licença : Nenhuma licença conhecida
  • Versão : 1.0.0
  • Divisões :
Dividir Exemplos
'test' 10.000
'train' 1999998
  • Características : 
{
    "question": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "answer": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    }
}

números__base_conversão

Use o seguinte comando para carregar este conjunto de dados no TFDS:

ds = tfds.load('huggingface:math_dataset/numbers__base_conversion')
  • Descrição :
Mathematics database.

This dataset code generates mathematical question and answer pairs,
from a range of question types at roughly school-level difficulty.
This is designed to test the mathematical learning and algebraic
reasoning skills of learning models.

Original paper: Analysing Mathematical Reasoning Abilities of Neural Models
(Saxton, Grefenstette, Hill, Kohli).

Example usage:
train_examples, val_examples = datasets.load_dataset(
    'math_dataset/arithmetic__mul',
    split=['train', 'test'],
    as_supervised=True)
  • Licença : Nenhuma licença conhecida
  • Versão : 1.0.0
  • Divisões :
Dividir Exemplos
'test' 10.000
'train' 1999998
  • Características : 
{
    "question": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "answer": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    }
}

números__div_restante

Use o seguinte comando para carregar este conjunto de dados no TFDS:

ds = tfds.load('huggingface:math_dataset/numbers__div_remainder')
  • Descrição :
Mathematics database.

This dataset code generates mathematical question and answer pairs,
from a range of question types at roughly school-level difficulty.
This is designed to test the mathematical learning and algebraic
reasoning skills of learning models.

Original paper: Analysing Mathematical Reasoning Abilities of Neural Models
(Saxton, Grefenstette, Hill, Kohli).

Example usage:
train_examples, val_examples = datasets.load_dataset(
    'math_dataset/arithmetic__mul',
    split=['train', 'test'],
    as_supervised=True)
  • Licença : Nenhuma licença conhecida
  • Versão : 1.0.0
  • Divisões :
Dividir Exemplos
'test' 10.000
'train' 1999998
  • Características : 
{
    "question": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "answer": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    }
}

números__div_remainder_composto

Use o seguinte comando para carregar este conjunto de dados no TFDS:

ds = tfds.load('huggingface:math_dataset/numbers__div_remainder_composed')
  • Descrição :
Mathematics database.

This dataset code generates mathematical question and answer pairs,
from a range of question types at roughly school-level difficulty.
This is designed to test the mathematical learning and algebraic
reasoning skills of learning models.

Original paper: Analysing Mathematical Reasoning Abilities of Neural Models
(Saxton, Grefenstette, Hill, Kohli).

Example usage:
train_examples, val_examples = datasets.load_dataset(
    'math_dataset/arithmetic__mul',
    split=['train', 'test'],
    as_supervised=True)
  • Licença : Nenhuma licença conhecida
  • Versão : 1.0.0
  • Divisões :
Dividir Exemplos
'test' 10.000
'train' 1999998
  • Características : 
{
    "question": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "answer": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    }
}

números__gcd

Use o seguinte comando para carregar este conjunto de dados no TFDS:

ds = tfds.load('huggingface:math_dataset/numbers__gcd')
  • Descrição :
Mathematics database.

This dataset code generates mathematical question and answer pairs,
from a range of question types at roughly school-level difficulty.
This is designed to test the mathematical learning and algebraic
reasoning skills of learning models.

Original paper: Analysing Mathematical Reasoning Abilities of Neural Models
(Saxton, Grefenstette, Hill, Kohli).

Example usage:
train_examples, val_examples = datasets.load_dataset(
    'math_dataset/arithmetic__mul',
    split=['train', 'test'],
    as_supervised=True)
  • Licença : Nenhuma licença conhecida
  • Versão : 1.0.0
  • Divisões :
Dividir Exemplos
'test' 10.000
'train' 1999998
  • Características : 
{
    "question": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "answer": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    }
}

números__gcd_composto

Use o seguinte comando para carregar este conjunto de dados no TFDS:

ds = tfds.load('huggingface:math_dataset/numbers__gcd_composed')
  • Descrição :
Mathematics database.

This dataset code generates mathematical question and answer pairs,
from a range of question types at roughly school-level difficulty.
This is designed to test the mathematical learning and algebraic
reasoning skills of learning models.

Original paper: Analysing Mathematical Reasoning Abilities of Neural Models
(Saxton, Grefenstette, Hill, Kohli).

Example usage:
train_examples, val_examples = datasets.load_dataset(
    'math_dataset/arithmetic__mul',
    split=['train', 'test'],
    as_supervised=True)
  • Licença : Nenhuma licença conhecida
  • Versão : 1.0.0
  • Divisões :
Dividir Exemplos
'test' 10.000
'train' 1999998
  • Características : 
{
    "question": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "answer": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    }
}

números__é_fator

Use o seguinte comando para carregar este conjunto de dados no TFDS:

ds = tfds.load('huggingface:math_dataset/numbers__is_factor')
  • Descrição :
Mathematics database.

This dataset code generates mathematical question and answer pairs,
from a range of question types at roughly school-level difficulty.
This is designed to test the mathematical learning and algebraic
reasoning skills of learning models.

Original paper: Analysing Mathematical Reasoning Abilities of Neural Models
(Saxton, Grefenstette, Hill, Kohli).

Example usage:
train_examples, val_examples = datasets.load_dataset(
    'math_dataset/arithmetic__mul',
    split=['train', 'test'],
    as_supervised=True)
  • Licença : Nenhuma licença conhecida
  • Versão : 1.0.0
  • Divisões :
Dividir Exemplos
'test' 10.000
'train' 1999998
  • Características : 
{
    "question": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "answer": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    }
}

números__é_fator_composto

Use o seguinte comando para carregar este conjunto de dados no TFDS:

ds = tfds.load('huggingface:math_dataset/numbers__is_factor_composed')
  • Descrição :
Mathematics database.

This dataset code generates mathematical question and answer pairs,
from a range of question types at roughly school-level difficulty.
This is designed to test the mathematical learning and algebraic
reasoning skills of learning models.

Original paper: Analysing Mathematical Reasoning Abilities of Neural Models
(Saxton, Grefenstette, Hill, Kohli).

Example usage:
train_examples, val_examples = datasets.load_dataset(
    'math_dataset/arithmetic__mul',
    split=['train', 'test'],
    as_supervised=True)
  • Licença : Nenhuma licença conhecida
  • Versão : 1.0.0
  • Divisões :
Dividir Exemplos
'test' 10.000
'train' 1999998
  • Características : 
{
    "question": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "answer": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    }
}

números__é_primo

Use o seguinte comando para carregar este conjunto de dados no TFDS:

ds = tfds.load('huggingface:math_dataset/numbers__is_prime')
  • Descrição :
Mathematics database.

This dataset code generates mathematical question and answer pairs,
from a range of question types at roughly school-level difficulty.
This is designed to test the mathematical learning and algebraic
reasoning skills of learning models.

Original paper: Analysing Mathematical Reasoning Abilities of Neural Models
(Saxton, Grefenstette, Hill, Kohli).

Example usage:
train_examples, val_examples = datasets.load_dataset(
    'math_dataset/arithmetic__mul',
    split=['train', 'test'],
    as_supervised=True)
  • Licença : Nenhuma licença conhecida
  • Versão : 1.0.0
  • Divisões :
Dividir Exemplos
'test' 10.000
'train' 1999998
  • Características : 
{
    "question": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "answer": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    }
}

números__is_prime_compostos

Use o seguinte comando para carregar este conjunto de dados no TFDS:

ds = tfds.load('huggingface:math_dataset/numbers__is_prime_composed')
  • Descrição :
Mathematics database.

This dataset code generates mathematical question and answer pairs,
from a range of question types at roughly school-level difficulty.
This is designed to test the mathematical learning and algebraic
reasoning skills of learning models.

Original paper: Analysing Mathematical Reasoning Abilities of Neural Models
(Saxton, Grefenstette, Hill, Kohli).

Example usage:
train_examples, val_examples = datasets.load_dataset(
    'math_dataset/arithmetic__mul',
    split=['train', 'test'],
    as_supervised=True)
  • Licença : Nenhuma licença conhecida
  • Versão : 1.0.0
  • Divisões :
Dividir Exemplos
'test' 10.000
'train' 1999998
  • Características : 
{
    "question": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "answer": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    }
}

números__lcm

Use o seguinte comando para carregar este conjunto de dados no TFDS:

ds = tfds.load('huggingface:math_dataset/numbers__lcm')
  • Descrição :
Mathematics database.

This dataset code generates mathematical question and answer pairs,
from a range of question types at roughly school-level difficulty.
This is designed to test the mathematical learning and algebraic
reasoning skills of learning models.

Original paper: Analysing Mathematical Reasoning Abilities of Neural Models
(Saxton, Grefenstette, Hill, Kohli).

Example usage:
train_examples, val_examples = datasets.load_dataset(
    'math_dataset/arithmetic__mul',
    split=['train', 'test'],
    as_supervised=True)
  • Licença : Nenhuma licença conhecida
  • Versão : 1.0.0
  • Divisões :
Dividir Exemplos
'test' 10.000
'train' 1999998
  • Características : 
{
    "question": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "answer": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    }
}

números__lcm_composto

Use o seguinte comando para carregar este conjunto de dados no TFDS:

ds = tfds.load('huggingface:math_dataset/numbers__lcm_composed')
  • Descrição :
Mathematics database.

This dataset code generates mathematical question and answer pairs,
from a range of question types at roughly school-level difficulty.
This is designed to test the mathematical learning and algebraic
reasoning skills of learning models.

Original paper: Analysing Mathematical Reasoning Abilities of Neural Models
(Saxton, Grefenstette, Hill, Kohli).

Example usage:
train_examples, val_examples = datasets.load_dataset(
    'math_dataset/arithmetic__mul',
    split=['train', 'test'],
    as_supervised=True)
  • Licença : Nenhuma licença conhecida
  • Versão : 1.0.0
  • Divisões :
Dividir Exemplos
'test' 10.000
'train' 1999998
  • Características : 
{
    "question": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "answer": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    }
}

números__list_prime_factors

Use o seguinte comando para carregar este conjunto de dados no TFDS:

ds = tfds.load('huggingface:math_dataset/numbers__list_prime_factors')
  • Descrição :
Mathematics database.

This dataset code generates mathematical question and answer pairs,
from a range of question types at roughly school-level difficulty.
This is designed to test the mathematical learning and algebraic
reasoning skills of learning models.

Original paper: Analysing Mathematical Reasoning Abilities of Neural Models
(Saxton, Grefenstette, Hill, Kohli).

Example usage:
train_examples, val_examples = datasets.load_dataset(
    'math_dataset/arithmetic__mul',
    split=['train', 'test'],
    as_supervised=True)
  • Licença : Nenhuma licença conhecida
  • Versão : 1.0.0
  • Divisões :
Dividir Exemplos
'test' 10.000
'train' 1999998
  • Características : 
{
    "question": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "answer": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    }
}

números__list_prime_factors_compostos

Use o seguinte comando para carregar este conjunto de dados no TFDS:

ds = tfds.load('huggingface:math_dataset/numbers__list_prime_factors_composed')
  • Descrição :
Mathematics database.

This dataset code generates mathematical question and answer pairs,
from a range of question types at roughly school-level difficulty.
This is designed to test the mathematical learning and algebraic
reasoning skills of learning models.

Original paper: Analysing Mathematical Reasoning Abilities of Neural Models
(Saxton, Grefenstette, Hill, Kohli).

Example usage:
train_examples, val_examples = datasets.load_dataset(
    'math_dataset/arithmetic__mul',
    split=['train', 'test'],
    as_supervised=True)
  • Licença : Nenhuma licença conhecida
  • Versão : 1.0.0
  • Divisões :
Dividir Exemplos
'test' 10.000
'train' 1999998
  • Características : 
{
    "question": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "answer": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    }
}

números__valor_local

Use o seguinte comando para carregar este conjunto de dados no TFDS:

ds = tfds.load('huggingface:math_dataset/numbers__place_value')
  • Descrição :
Mathematics database.

This dataset code generates mathematical question and answer pairs,
from a range of question types at roughly school-level difficulty.
This is designed to test the mathematical learning and algebraic
reasoning skills of learning models.

Original paper: Analysing Mathematical Reasoning Abilities of Neural Models
(Saxton, Grefenstette, Hill, Kohli).

Example usage:
train_examples, val_examples = datasets.load_dataset(
    'math_dataset/arithmetic__mul',
    split=['train', 'test'],
    as_supervised=True)
  • Licença : Nenhuma licença conhecida
  • Versão : 1.0.0
  • Divisões :
Dividir Exemplos
'test' 10.000
'train' 1999998
  • Características : 
{
    "question": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "answer": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    }
}

números__place_value_composto

Use o seguinte comando para carregar este conjunto de dados no TFDS:

ds = tfds.load('huggingface:math_dataset/numbers__place_value_composed')
  • Descrição :
Mathematics database.

This dataset code generates mathematical question and answer pairs,
from a range of question types at roughly school-level difficulty.
This is designed to test the mathematical learning and algebraic
reasoning skills of learning models.

Original paper: Analysing Mathematical Reasoning Abilities of Neural Models
(Saxton, Grefenstette, Hill, Kohli).

Example usage:
train_examples, val_examples = datasets.load_dataset(
    'math_dataset/arithmetic__mul',
    split=['train', 'test'],
    as_supervised=True)
  • Licença : Nenhuma licença conhecida
  • Versão : 1.0.0
  • Divisões :
Dividir Exemplos
'test' 10.000
'train' 1999998
  • Características : 
{
    "question": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "answer": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    }
}

números__número_redondo

Use o seguinte comando para carregar este conjunto de dados no TFDS:

ds = tfds.load('huggingface:math_dataset/numbers__round_number')
  • Descrição :
Mathematics database.

This dataset code generates mathematical question and answer pairs,
from a range of question types at roughly school-level difficulty.
This is designed to test the mathematical learning and algebraic
reasoning skills of learning models.

Original paper: Analysing Mathematical Reasoning Abilities of Neural Models
(Saxton, Grefenstette, Hill, Kohli).

Example usage:
train_examples, val_examples = datasets.load_dataset(
    'math_dataset/arithmetic__mul',
    split=['train', 'test'],
    as_supervised=True)
  • Licença : Nenhuma licença conhecida
  • Versão : 1.0.0
  • Divisões :
Dividir Exemplos
'test' 10.000
'train' 1999998
  • Características : 
{
    "question": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "answer": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    }
}

números__número_redondo_composto

Use o seguinte comando para carregar este conjunto de dados no TFDS:

ds = tfds.load('huggingface:math_dataset/numbers__round_number_composed')
  • Descrição :
Mathematics database.

This dataset code generates mathematical question and answer pairs,
from a range of question types at roughly school-level difficulty.
This is designed to test the mathematical learning and algebraic
reasoning skills of learning models.

Original paper: Analysing Mathematical Reasoning Abilities of Neural Models
(Saxton, Grefenstette, Hill, Kohli).

Example usage:
train_examples, val_examples = datasets.load_dataset(
    'math_dataset/arithmetic__mul',
    split=['train', 'test'],
    as_supervised=True)
  • Licença : Nenhuma licença conhecida
  • Versão : 1.0.0
  • Divisões :
Dividir Exemplos
'test' 10.000
'train' 1999998
  • Características : 
{
    "question": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "answer": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    }
}

polinômios__adicionar

Use o seguinte comando para carregar este conjunto de dados no TFDS:

ds = tfds.load('huggingface:math_dataset/polynomials__add')
  • Descrição :
Mathematics database.

This dataset code generates mathematical question and answer pairs,
from a range of question types at roughly school-level difficulty.
This is designed to test the mathematical learning and algebraic
reasoning skills of learning models.

Original paper: Analysing Mathematical Reasoning Abilities of Neural Models
(Saxton, Grefenstette, Hill, Kohli).

Example usage:
train_examples, val_examples = datasets.load_dataset(
    'math_dataset/arithmetic__mul',
    split=['train', 'test'],
    as_supervised=True)
  • Licença : Nenhuma licença conhecida
  • Versão : 1.0.0
  • Divisões :
Dividir Exemplos
'test' 10.000
'train' 1999998
  • Características : 
{
    "question": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "answer": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    }
}

polinômios__coeficiente_nomeado

Use o seguinte comando para carregar este conjunto de dados no TFDS:

ds = tfds.load('huggingface:math_dataset/polynomials__coefficient_named')
  • Descrição :
Mathematics database.

This dataset code generates mathematical question and answer pairs,
from a range of question types at roughly school-level difficulty.
This is designed to test the mathematical learning and algebraic
reasoning skills of learning models.

Original paper: Analysing Mathematical Reasoning Abilities of Neural Models
(Saxton, Grefenstette, Hill, Kohli).

Example usage:
train_examples, val_examples = datasets.load_dataset(
    'math_dataset/arithmetic__mul',
    split=['train', 'test'],
    as_supervised=True)
  • Licença : Nenhuma licença conhecida
  • Versão : 1.0.0
  • Divisões :
Dividir Exemplos
'test' 10.000
'train' 1999998
  • Características : 
{
    "question": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "answer": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    }
}

polinômios__coletar

Use o seguinte comando para carregar este conjunto de dados no TFDS:

ds = tfds.load('huggingface:math_dataset/polynomials__collect')
  • Descrição :
Mathematics database.

This dataset code generates mathematical question and answer pairs,
from a range of question types at roughly school-level difficulty.
This is designed to test the mathematical learning and algebraic
reasoning skills of learning models.

Original paper: Analysing Mathematical Reasoning Abilities of Neural Models
(Saxton, Grefenstette, Hill, Kohli).

Example usage:
train_examples, val_examples = datasets.load_dataset(
    'math_dataset/arithmetic__mul',
    split=['train', 'test'],
    as_supervised=True)
  • Licença : Nenhuma licença conhecida
  • Versão : 1.0.0
  • Divisões :
Dividir Exemplos
'test' 10.000
'train' 1999998
  • Características : 
{
    "question": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "answer": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    }
}

polinômios__compor

Use o seguinte comando para carregar este conjunto de dados no TFDS:

ds = tfds.load('huggingface:math_dataset/polynomials__compose')
  • Descrição :
Mathematics database.

This dataset code generates mathematical question and answer pairs,
from a range of question types at roughly school-level difficulty.
This is designed to test the mathematical learning and algebraic
reasoning skills of learning models.

Original paper: Analysing Mathematical Reasoning Abilities of Neural Models
(Saxton, Grefenstette, Hill, Kohli).

Example usage:
train_examples, val_examples = datasets.load_dataset(
    'math_dataset/arithmetic__mul',
    split=['train', 'test'],
    as_supervised=True)
  • Licença : Nenhuma licença conhecida
  • Versão : 1.0.0
  • Divisões :
Dividir Exemplos
'test' 10.000
'train' 1999998
  • Características : 
{
    "question": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "answer": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    }
}

polinômios__avaliar

Use o seguinte comando para carregar este conjunto de dados no TFDS:

ds = tfds.load('huggingface:math_dataset/polynomials__evaluate')
  • Descrição :
Mathematics database.

This dataset code generates mathematical question and answer pairs,
from a range of question types at roughly school-level difficulty.
This is designed to test the mathematical learning and algebraic
reasoning skills of learning models.

Original paper: Analysing Mathematical Reasoning Abilities of Neural Models
(Saxton, Grefenstette, Hill, Kohli).

Example usage:
train_examples, val_examples = datasets.load_dataset(
    'math_dataset/arithmetic__mul',
    split=['train', 'test'],
    as_supervised=True)
  • Licença : Nenhuma licença conhecida
  • Versão : 1.0.0
  • Divisões :
Dividir Exemplos
'test' 10.000
'train' 1999998
  • Características : 
{
    "question": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "answer": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    }
}

polinômios__avaliar_composto

Use o seguinte comando para carregar este conjunto de dados no TFDS:

ds = tfds.load('huggingface:math_dataset/polynomials__evaluate_composed')
  • Descrição :
Mathematics database.

This dataset code generates mathematical question and answer pairs,
from a range of question types at roughly school-level difficulty.
This is designed to test the mathematical learning and algebraic
reasoning skills of learning models.

Original paper: Analysing Mathematical Reasoning Abilities of Neural Models
(Saxton, Grefenstette, Hill, Kohli).

Example usage:
train_examples, val_examples = datasets.load_dataset(
    'math_dataset/arithmetic__mul',
    split=['train', 'test'],
    as_supervised=True)
  • Licença : Nenhuma licença conhecida
  • Versão : 1.0.0
  • Divisões :
Dividir Exemplos
'test' 10.000
'train' 1999998
  • Características : 
{
    "question": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "answer": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    }
}

polinômios__expandir

Use o seguinte comando para carregar este conjunto de dados no TFDS:

ds = tfds.load('huggingface:math_dataset/polynomials__expand')
  • Descrição :
Mathematics database.

This dataset code generates mathematical question and answer pairs,
from a range of question types at roughly school-level difficulty.
This is designed to test the mathematical learning and algebraic
reasoning skills of learning models.

Original paper: Analysing Mathematical Reasoning Abilities of Neural Models
(Saxton, Grefenstette, Hill, Kohli).

Example usage:
train_examples, val_examples = datasets.load_dataset(
    'math_dataset/arithmetic__mul',
    split=['train', 'test'],
    as_supervised=True)
  • Licença : Nenhuma licença conhecida
  • Versão : 1.0.0
  • Divisões :
Dividir Exemplos
'test' 10.000
'train' 1999998
  • Características : 
{
    "question": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "answer": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    }
}

polinômios__simplify_power

Use o seguinte comando para carregar este conjunto de dados no TFDS:

ds = tfds.load('huggingface:math_dataset/polynomials__simplify_power')
  • Descrição :
Mathematics database.

This dataset code generates mathematical question and answer pairs,
from a range of question types at roughly school-level difficulty.
This is designed to test the mathematical learning and algebraic
reasoning skills of learning models.

Original paper: Analysing Mathematical Reasoning Abilities of Neural Models
(Saxton, Grefenstette, Hill, Kohli).

Example usage:
train_examples, val_examples = datasets.load_dataset(
    'math_dataset/arithmetic__mul',
    split=['train', 'test'],
    as_supervised=True)
  • Licença : Nenhuma licença conhecida
  • Versão : 1.0.0
  • Divisões :
Dividir Exemplos
'test' 10.000
'train' 1999998
  • Características : 
{
    "question": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "answer": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    }
}

probabilidade__swr_p_level_set

Use o seguinte comando para carregar este conjunto de dados no TFDS:

ds = tfds.load('huggingface:math_dataset/probability__swr_p_level_set')
  • Descrição :
Mathematics database.

This dataset code generates mathematical question and answer pairs,
from a range of question types at roughly school-level difficulty.
This is designed to test the mathematical learning and algebraic
reasoning skills of learning models.

Original paper: Analysing Mathematical Reasoning Abilities of Neural Models
(Saxton, Grefenstette, Hill, Kohli).

Example usage:
train_examples, val_examples = datasets.load_dataset(
    'math_dataset/arithmetic__mul',
    split=['train', 'test'],
    as_supervised=True)
  • Licença : Nenhuma licença conhecida
  • Versão : 1.0.0
  • Divisões :
Dividir Exemplos
'test' 10.000
'train' 1999998
  • Características : 
{
    "question": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "answer": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    }
}

probabilidade__swr_p_sequence

Use o seguinte comando para carregar este conjunto de dados no TFDS:

ds = tfds.load('huggingface:math_dataset/probability__swr_p_sequence')
  • Descrição :
Mathematics database.

This dataset code generates mathematical question and answer pairs,
from a range of question types at roughly school-level difficulty.
This is designed to test the mathematical learning and algebraic
reasoning skills of learning models.

Original paper: Analysing Mathematical Reasoning Abilities of Neural Models
(Saxton, Grefenstette, Hill, Kohli).

Example usage:
train_examples, val_examples = datasets.load_dataset(
    'math_dataset/arithmetic__mul',
    split=['train', 'test'],
    as_supervised=True)
  • Licença : Nenhuma licença conhecida
  • Versão : 1.0.0
  • Divisões :
Dividir Exemplos
'test' 10.000
'train' 1999998
  • Características :
{
    "question": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "answer": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    }
}