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"
}
}