参考文献:
代数__linear_1d
次のコマンドを使用して、このデータセットを TFDS にロードします。
ds = tfds.load('huggingface:math_dataset/algebra__linear_1d')
- 説明：
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)
- ライセンス: 既知のライセンスはありません
- バージョン: 1.0.0
- 分割:
| スプリット | 例 |
|---|---|
'test' | 10000 |
'train' | 1999998 |
- 特徴：
{
"question": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"answer": {
"dtype": "string",
"id": null,
"_type": "Value"
}
}
代数__linear_1d_comped
次のコマンドを使用して、このデータセットを TFDS にロードします。
ds = tfds.load('huggingface:math_dataset/algebra__linear_1d_composed')
- 説明：
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)
- ライセンス: 既知のライセンスはありません
- バージョン: 1.0.0
- 分割:
| スプリット | 例 |
|---|---|
'test' | 10000 |
'train' | 1999998 |
- 特徴：
{
"question": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"answer": {
"dtype": "string",
"id": null,
"_type": "Value"
}
}
代数__linear_2d
次のコマンドを使用して、このデータセットを TFDS にロードします。
ds = tfds.load('huggingface:math_dataset/algebra__linear_2d')
- 説明：
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)
- ライセンス: 既知のライセンスはありません
- バージョン: 1.0.0
- 分割:
| スプリット | 例 |
|---|---|
'test' | 10000 |
'train' | 1999998 |
- 特徴：
{
"question": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"answer": {
"dtype": "string",
"id": null,
"_type": "Value"
}
}
代数__linear_2d_comped
次のコマンドを使用して、このデータセットを TFDS にロードします。
ds = tfds.load('huggingface:math_dataset/algebra__linear_2d_composed')
- 説明：
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)
- ライセンス: 既知のライセンスはありません
- バージョン: 1.0.0
- 分割:
| スプリット | 例 |
|---|---|
'test' | 10000 |
'train' | 1999998 |
- 特徴：
{
"question": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"answer": {
"dtype": "string",
"id": null,
"_type": "Value"
}
}
代数__多項式根
次のコマンドを使用して、このデータセットを TFDS にロードします。
ds = tfds.load('huggingface:math_dataset/algebra__polynomial_roots')
- 説明：
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)
- ライセンス: 既知のライセンスはありません
- バージョン: 1.0.0
- 分割:
| スプリット | 例 |
|---|---|
'test' | 10000 |
'train' | 1999998 |
- 特徴：
{
"question": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"answer": {
"dtype": "string",
"id": null,
"_type": "Value"
}
}
代数__多項式根_合成
次のコマンドを使用して、このデータセットを TFDS にロードします。
ds = tfds.load('huggingface:math_dataset/algebra__polynomial_roots_composed')
- 説明：
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)
- ライセンス: 既知のライセンスはありません
- バージョン: 1.0.0
- 分割:
| スプリット | 例 |
|---|---|
'test' | 10000 |
'train' | 1999998 |
- 特徴：
{
"question": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"answer": {
"dtype": "string",
"id": null,
"_type": "Value"
}
}
algebra__sequence_next_term
次のコマンドを使用して、このデータセットを TFDS にロードします。
ds = tfds.load('huggingface:math_dataset/algebra__sequence_next_term')
- 説明：
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)
- ライセンス: 既知のライセンスはありません
- バージョン: 1.0.0
- 分割:
| スプリット | 例 |
|---|---|
'test' | 10000 |
'train' | 1999998 |
- 特徴：
{
"question": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"answer": {
"dtype": "string",
"id": null,
"_type": "Value"
}
}
algebra__sequence_nth_term
次のコマンドを使用して、このデータセットを TFDS にロードします。
ds = tfds.load('huggingface:math_dataset/algebra__sequence_nth_term')
- 説明：
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)
- ライセンス: 既知のライセンスはありません
- バージョン: 1.0.0
- 分割:
| スプリット | 例 |
|---|---|
'test' | 10000 |
'train' | 1999998 |
- 特徴：
{
"question": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"answer": {
"dtype": "string",
"id": null,
"_type": "Value"
}
}
算術__add_or_sub
次のコマンドを使用して、このデータセットを TFDS にロードします。
ds = tfds.load('huggingface:math_dataset/arithmetic__add_or_sub')
- 説明：
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)
- ライセンス: 既知のライセンスはありません
- バージョン: 1.0.0
- 分割:
| スプリット | 例 |
|---|---|
'test' | 10000 |
'train' | 1999998 |
- 特徴：
{
"question": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"answer": {
"dtype": "string",
"id": null,
"_type": "Value"
}
}
arithmetic__add_or_sub_in_base
次のコマンドを使用して、このデータセットを TFDS にロードします。
ds = tfds.load('huggingface:math_dataset/arithmetic__add_or_sub_in_base')
- 説明：
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)
- ライセンス: 既知のライセンスはありません
- バージョン: 1.0.0
- 分割:
| スプリット | 例 |
|---|---|
'test' | 10000 |
'train' | 1999998 |
- 特徴：
{
"question": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"answer": {
"dtype": "string",
"id": null,
"_type": "Value"
}
}
算術__add_sub_multiple
次のコマンドを使用して、このデータセットを TFDS にロードします。
ds = tfds.load('huggingface:math_dataset/arithmetic__add_sub_multiple')
- 説明：
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)
- ライセンス: 既知のライセンスはありません
- バージョン: 1.0.0
- 分割:
| スプリット | 例 |
|---|---|
'test' | 10000 |
'train' | 1999998 |
- 特徴：
{
"question": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"answer": {
"dtype": "string",
"id": null,
"_type": "Value"
}
}
算術__div
次のコマンドを使用して、このデータセットを TFDS にロードします。
ds = tfds.load('huggingface:math_dataset/arithmetic__div')
- 説明：
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)
- ライセンス: 既知のライセンスはありません
- バージョン: 1.0.0
- 分割:
| スプリット | 例 |
|---|---|
'test' | 10000 |
'train' | 1999998 |
- 特徴：
{
"question": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"answer": {
"dtype": "string",
"id": null,
"_type": "Value"
}
}
算術__混合
次のコマンドを使用して、このデータセットを TFDS にロードします。
ds = tfds.load('huggingface:math_dataset/arithmetic__mixed')
- 説明：
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)
- ライセンス: 既知のライセンスはありません
- バージョン: 1.0.0
- 分割:
| スプリット | 例 |
|---|---|
'test' | 10000 |
'train' | 1999998 |
- 特徴：
{
"question": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"answer": {
"dtype": "string",
"id": null,
"_type": "Value"
}
}
算術__mul
次のコマンドを使用して、このデータセットを TFDS にロードします。
ds = tfds.load('huggingface:math_dataset/arithmetic__mul')
- 説明：
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)
- ライセンス: 既知のライセンスはありません
- バージョン: 1.0.0
- 分割:
| スプリット | 例 |
|---|---|
'test' | 10000 |
'train' | 1999998 |
- 特徴：
{
"question": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"answer": {
"dtype": "string",
"id": null,
"_type": "Value"
}
}
算術__mul_div_multiple
次のコマンドを使用して、このデータセットを TFDS にロードします。
ds = tfds.load('huggingface:math_dataset/arithmetic__mul_div_multiple')
- 説明：
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)
- ライセンス: 既知のライセンスはありません
- バージョン: 1.0.0
- 分割:
| スプリット | 例 |
|---|---|
'test' | 10000 |
'train' | 1999998 |
- 特徴：
{
"question": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"answer": {
"dtype": "string",
"id": null,
"_type": "Value"
}
}
arithmetic__nearest_integer_root
次のコマンドを使用して、このデータセットを TFDS にロードします。
ds = tfds.load('huggingface:math_dataset/arithmetic__nearest_integer_root')
- 説明：
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)
- ライセンス: 既知のライセンスはありません
- バージョン: 1.0.0
- 分割:
| スプリット | 例 |
|---|---|
'test' | 10000 |
'train' | 1999998 |
- 特徴：
{
"question": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"answer": {
"dtype": "string",
"id": null,
"_type": "Value"
}
}
arithmetic__simplify_surd
次のコマンドを使用して、このデータセットを TFDS にロードします。
ds = tfds.load('huggingface:math_dataset/arithmetic__simplify_surd')
- 説明：
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)
- ライセンス: 既知のライセンスはありません
- バージョン: 1.0.0
- 分割:
| スプリット | 例 |
|---|---|
'test' | 10000 |
'train' | 1999998 |
- 特徴：
{
"question": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"answer": {
"dtype": "string",
"id": null,
"_type": "Value"
}
}
微積分__微分
次のコマンドを使用して、このデータセットを TFDS にロードします。
ds = tfds.load('huggingface:math_dataset/calculus__differentiate')
- 説明：
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)
- ライセンス: 既知のライセンスはありません
- バージョン: 1.0.0
- 分割:
| スプリット | 例 |
|---|---|
'test' | 10000 |
'train' | 1999998 |
- 特徴：
{
"question": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"answer": {
"dtype": "string",
"id": null,
"_type": "Value"
}
}
微積分__微分_合成
次のコマンドを使用して、このデータセットを TFDS にロードします。
ds = tfds.load('huggingface:math_dataset/calculus__differentiate_composed')
- 説明：
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)
- ライセンス: 既知のライセンスはありません
- バージョン: 1.0.0
- 分割:
| スプリット | 例 |
|---|---|
'test' | 10000 |
'train' | 1999998 |
- 特徴：
{
"question": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"answer": {
"dtype": "string",
"id": null,
"_type": "Value"
}
}
比較__最も近い
次のコマンドを使用して、このデータセットを TFDS にロードします。
ds = tfds.load('huggingface:math_dataset/comparison__closest')
- 説明：
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)
- ライセンス: 既知のライセンスはありません
- バージョン: 1.0.0
- 分割:
| スプリット | 例 |
|---|---|
'test' | 10000 |
'train' | 1999998 |
- 特徴：
{
"question": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"answer": {
"dtype": "string",
"id": null,
"_type": "Value"
}
}
比較__最も近い_構成
次のコマンドを使用して、このデータセットを TFDS にロードします。
ds = tfds.load('huggingface:math_dataset/comparison__closest_composed')
- 説明：
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)
- ライセンス: 既知のライセンスはありません
- バージョン: 1.0.0
- 分割:
| スプリット | 例 |
|---|---|
'test' | 10000 |
'train' | 1999998 |
- 特徴：
{
"question": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"answer": {
"dtype": "string",
"id": null,
"_type": "Value"
}
}
比較__kth_biggest
次のコマンドを使用して、このデータセットを TFDS にロードします。
ds = tfds.load('huggingface:math_dataset/comparison__kth_biggest')
- 説明：
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)
- ライセンス: 既知のライセンスはありません
- バージョン: 1.0.0
- 分割:
| スプリット | 例 |
|---|---|
'test' | 10000 |
'train' | 1999998 |
- 特徴：
{
"question": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"answer": {
"dtype": "string",
"id": null,
"_type": "Value"
}
}
比較__kth_biggest_comped
次のコマンドを使用して、このデータセットを TFDS にロードします。
ds = tfds.load('huggingface:math_dataset/comparison__kth_biggest_composed')
- 説明：
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)
- ライセンス: 既知のライセンスはありません
- バージョン: 1.0.0
- 分割:
| スプリット | 例 |
|---|---|
'test' | 10000 |
'train' | 1999998 |
- 特徴：
{
"question": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"answer": {
"dtype": "string",
"id": null,
"_type": "Value"
}
}
比較__ペア
次のコマンドを使用して、このデータセットを TFDS にロードします。
ds = tfds.load('huggingface:math_dataset/comparison__pair')
- 説明：
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)
- ライセンス: 既知のライセンスはありません
- バージョン: 1.0.0
- 分割:
| スプリット | 例 |
|---|---|
'test' | 10000 |
'train' | 1999998 |
- 特徴：
{
"question": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"answer": {
"dtype": "string",
"id": null,
"_type": "Value"
}
}
比較__ペア_構成
次のコマンドを使用して、このデータセットを TFDS にロードします。
ds = tfds.load('huggingface:math_dataset/comparison__pair_composed')
- 説明：
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)
- ライセンス: 既知のライセンスはありません
- バージョン: 1.0.0
- 分割:
| スプリット | 例 |
|---|---|
'test' | 10000 |
'train' | 1999998 |
- 特徴：
{
"question": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"answer": {
"dtype": "string",
"id": null,
"_type": "Value"
}
}
比較__ソート
次のコマンドを使用して、このデータセットを TFDS にロードします。
ds = tfds.load('huggingface:math_dataset/comparison__sort')
- 説明：
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)
- ライセンス: 既知のライセンスはありません
- バージョン: 1.0.0
- 分割:
| スプリット | 例 |
|---|---|
'test' | 10000 |
'train' | 1999998 |
- 特徴：
{
"question": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"answer": {
"dtype": "string",
"id": null,
"_type": "Value"
}
}
比較__sort_comped
次のコマンドを使用して、このデータセットを TFDS にロードします。
ds = tfds.load('huggingface:math_dataset/comparison__sort_composed')
- 説明：
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)
- ライセンス: 既知のライセンスはありません
- バージョン: 1.0.0
- 分割:
| スプリット | 例 |
|---|---|
'test' | 10000 |
'train' | 1999998 |
- 特徴：
{
"question": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"answer": {
"dtype": "string",
"id": null,
"_type": "Value"
}
}
測定__変換
次のコマンドを使用して、このデータセットを TFDS にロードします。
ds = tfds.load('huggingface:math_dataset/measurement__conversion')
- 説明：
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)
- ライセンス: 既知のライセンスはありません
- バージョン: 1.0.0
- 分割:
| スプリット | 例 |
|---|---|
'test' | 10000 |
'train' | 1999998 |
- 特徴：
{
"question": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"answer": {
"dtype": "string",
"id": null,
"_type": "Value"
}
}
測定__時間
次のコマンドを使用して、このデータセットを TFDS にロードします。
ds = tfds.load('huggingface:math_dataset/measurement__time')
- 説明：
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)
- ライセンス: 既知のライセンスはありません
- バージョン: 1.0.0
- 分割:
| スプリット | 例 |
|---|---|
'test' | 10000 |
'train' | 1999998 |
- 特徴：
{
"question": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"answer": {
"dtype": "string",
"id": null,
"_type": "Value"
}
}
数値__base_conversion
次のコマンドを使用して、このデータセットを TFDS にロードします。
ds = tfds.load('huggingface:math_dataset/numbers__base_conversion')
- 説明：
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)
- ライセンス: 既知のライセンスはありません
- バージョン: 1.0.0
- 分割:
| スプリット | 例 |
|---|---|
'test' | 10000 |
'train' | 1999998 |
- 特徴：
{
"question": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"answer": {
"dtype": "string",
"id": null,
"_type": "Value"
}
}
数値__div_remainder
次のコマンドを使用して、このデータセットを TFDS にロードします。
ds = tfds.load('huggingface:math_dataset/numbers__div_remainder')
- 説明：
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)
- ライセンス: 既知のライセンスはありません
- バージョン: 1.0.0
- 分割:
| スプリット | 例 |
|---|---|
'test' | 10000 |
'train' | 1999998 |
- 特徴：
{
"question": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"answer": {
"dtype": "string",
"id": null,
"_type": "Value"
}
}
数値__div_remainder_comped
次のコマンドを使用して、このデータセットを TFDS にロードします。
ds = tfds.load('huggingface:math_dataset/numbers__div_remainder_composed')
- 説明：
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)
- ライセンス: 既知のライセンスはありません
- バージョン: 1.0.0
- 分割:
| スプリット | 例 |
|---|---|
'test' | 10000 |
'train' | 1999998 |
- 特徴：
{
"question": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"answer": {
"dtype": "string",
"id": null,
"_type": "Value"
}
}
数値__gcd
次のコマンドを使用して、このデータセットを TFDS にロードします。
ds = tfds.load('huggingface:math_dataset/numbers__gcd')
- 説明：
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)
- ライセンス: 既知のライセンスはありません
- バージョン: 1.0.0
- 分割:
| スプリット | 例 |
|---|---|
'test' | 10000 |
'train' | 1999998 |
- 特徴：
{
"question": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"answer": {
"dtype": "string",
"id": null,
"_type": "Value"
}
}
数値__gcd_comped
次のコマンドを使用して、このデータセットを TFDS にロードします。
ds = tfds.load('huggingface:math_dataset/numbers__gcd_composed')
- 説明：
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)
- ライセンス: 既知のライセンスはありません
- バージョン: 1.0.0
- 分割:
| スプリット | 例 |
|---|---|
'test' | 10000 |
'train' | 1999998 |
- 特徴：
{
"question": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"answer": {
"dtype": "string",
"id": null,
"_type": "Value"
}
}
数値__is_factor
次のコマンドを使用して、このデータセットを TFDS にロードします。
ds = tfds.load('huggingface:math_dataset/numbers__is_factor')
- 説明：
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)
- ライセンス: 既知のライセンスはありません
- バージョン: 1.0.0
- 分割:
| スプリット | 例 |
|---|---|
'test' | 10000 |
'train' | 1999998 |
- 特徴：
{
"question": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"answer": {
"dtype": "string",
"id": null,
"_type": "Value"
}
}
数値__is_factor_comped
次のコマンドを使用して、このデータセットを TFDS にロードします。
ds = tfds.load('huggingface:math_dataset/numbers__is_factor_composed')
- 説明：
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)
- ライセンス: 既知のライセンスはありません
- バージョン: 1.0.0
- 分割:
| スプリット | 例 |
|---|---|
'test' | 10000 |
'train' | 1999998 |
- 特徴：
{
"question": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"answer": {
"dtype": "string",
"id": null,
"_type": "Value"
}
}
数値__is_prime
次のコマンドを使用して、このデータセットを TFDS にロードします。
ds = tfds.load('huggingface:math_dataset/numbers__is_prime')
- 説明：
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)
- ライセンス: 既知のライセンスはありません
- バージョン: 1.0.0
- 分割:
| スプリット | 例 |
|---|---|
'test' | 10000 |
'train' | 1999998 |
- 特徴：
{
"question": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"answer": {
"dtype": "string",
"id": null,
"_type": "Value"
}
}
数値__is_prime_comped
次のコマンドを使用して、このデータセットを TFDS にロードします。
ds = tfds.load('huggingface:math_dataset/numbers__is_prime_composed')
- 説明：
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)
- ライセンス: 既知のライセンスはありません
- バージョン: 1.0.0
- 分割:
| スプリット | 例 |
|---|---|
'test' | 10000 |
'train' | 1999998 |
- 特徴：
{
"question": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"answer": {
"dtype": "string",
"id": null,
"_type": "Value"
}
}
数値__lcm
次のコマンドを使用して、このデータセットを TFDS にロードします。
ds = tfds.load('huggingface:math_dataset/numbers__lcm')
- 説明：
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)
- ライセンス: 既知のライセンスはありません
- バージョン: 1.0.0
- 分割:
| スプリット | 例 |
|---|---|
'test' | 10000 |
'train' | 1999998 |
- 特徴：
{
"question": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"answer": {
"dtype": "string",
"id": null,
"_type": "Value"
}
}
数値__lcm_comped
次のコマンドを使用して、このデータセットを TFDS にロードします。
ds = tfds.load('huggingface:math_dataset/numbers__lcm_composed')
- 説明：
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)
- ライセンス: 既知のライセンスはありません
- バージョン: 1.0.0
- 分割:
| スプリット | 例 |
|---|---|
'test' | 10000 |
'train' | 1999998 |
- 特徴：
{
"question": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"answer": {
"dtype": "string",
"id": null,
"_type": "Value"
}
}
数値__list_prime_factors
次のコマンドを使用して、このデータセットを TFDS にロードします。
ds = tfds.load('huggingface:math_dataset/numbers__list_prime_factors')
- 説明：
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)
- ライセンス: 既知のライセンスはありません
- バージョン: 1.0.0
- 分割:
| スプリット | 例 |
|---|---|
'test' | 10000 |
'train' | 1999998 |
- 特徴：
{
"question": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"answer": {
"dtype": "string",
"id": null,
"_type": "Value"
}
}
数値__list_prime_factors_comped
次のコマンドを使用して、このデータセットを TFDS にロードします。
ds = tfds.load('huggingface:math_dataset/numbers__list_prime_factors_composed')
- 説明：
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)
- ライセンス: 既知のライセンスはありません
- バージョン: 1.0.0
- 分割:
| スプリット | 例 |
|---|---|
'test' | 10000 |
'train' | 1999998 |
- 特徴：
{
"question": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"answer": {
"dtype": "string",
"id": null,
"_type": "Value"
}
}
数値__場所_値
次のコマンドを使用して、このデータセットを TFDS にロードします。
ds = tfds.load('huggingface:math_dataset/numbers__place_value')
- 説明：
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)
- ライセンス: 既知のライセンスはありません
- バージョン: 1.0.0
- 分割:
| スプリット | 例 |
|---|---|
'test' | 10000 |
'train' | 1999998 |
- 特徴：
{
"question": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"answer": {
"dtype": "string",
"id": null,
"_type": "Value"
}
}
数値_場所_値_構成
次のコマンドを使用して、このデータセットを TFDS にロードします。
ds = tfds.load('huggingface:math_dataset/numbers__place_value_composed')
- 説明：
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)
- ライセンス: 既知のライセンスはありません
- バージョン: 1.0.0
- 分割:
| スプリット | 例 |
|---|---|
'test' | 10000 |
'train' | 1999998 |
- 特徴：
{
"question": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"answer": {
"dtype": "string",
"id": null,
"_type": "Value"
}
}
数値__round_number
次のコマンドを使用して、このデータセットを TFDS にロードします。
ds = tfds.load('huggingface:math_dataset/numbers__round_number')
- 説明：
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)
- ライセンス: 既知のライセンスはありません
- バージョン: 1.0.0
- 分割:
| スプリット | 例 |
|---|---|
'test' | 10000 |
'train' | 1999998 |
- 特徴：
{
"question": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"answer": {
"dtype": "string",
"id": null,
"_type": "Value"
}
}
数字__round_number_comped
次のコマンドを使用して、このデータセットを TFDS にロードします。
ds = tfds.load('huggingface:math_dataset/numbers__round_number_composed')
- 説明：
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)
- ライセンス: 既知のライセンスはありません
- バージョン: 1.0.0
- 分割:
| スプリット | 例 |
|---|---|
'test' | 10000 |
'train' | 1999998 |
- 特徴：
{
"question": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"answer": {
"dtype": "string",
"id": null,
"_type": "Value"
}
}
多項式__add
次のコマンドを使用して、このデータセットを TFDS にロードします。
ds = tfds.load('huggingface:math_dataset/polynomials__add')
- 説明：
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)
- ライセンス: 既知のライセンスはありません
- バージョン: 1.0.0
- 分割:
| スプリット | 例 |
|---|---|
'test' | 10000 |
'train' | 1999998 |
- 特徴：
{
"question": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"answer": {
"dtype": "string",
"id": null,
"_type": "Value"
}
}
多項式__coefficient_named
次のコマンドを使用して、このデータセットを TFDS にロードします。
ds = tfds.load('huggingface:math_dataset/polynomials__coefficient_named')
- 説明：
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)
- ライセンス: 既知のライセンスはありません
- バージョン: 1.0.0
- 分割:
| スプリット | 例 |
|---|---|
'test' | 10000 |
'train' | 1999998 |
- 特徴：
{
"question": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"answer": {
"dtype": "string",
"id": null,
"_type": "Value"
}
}
多項式__collect
次のコマンドを使用して、このデータセットを TFDS にロードします。
ds = tfds.load('huggingface:math_dataset/polynomials__collect')
- 説明：
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)
- ライセンス: 既知のライセンスはありません
- バージョン: 1.0.0
- 分割:
| スプリット | 例 |
|---|---|
'test' | 10000 |
'train' | 1999998 |
- 特徴：
{
"question": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"answer": {
"dtype": "string",
"id": null,
"_type": "Value"
}
}
多項式__compose
次のコマンドを使用して、このデータセットを TFDS にロードします。
ds = tfds.load('huggingface:math_dataset/polynomials__compose')
- 説明：
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)
- ライセンス: 既知のライセンスはありません
- バージョン: 1.0.0
- 分割:
| スプリット | 例 |
|---|---|
'test' | 10000 |
'train' | 1999998 |
- 特徴：
{
"question": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"answer": {
"dtype": "string",
"id": null,
"_type": "Value"
}
}
多項式__evaluate
次のコマンドを使用して、このデータセットを TFDS にロードします。
ds = tfds.load('huggingface:math_dataset/polynomials__evaluate')
- 説明：
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)
- ライセンス: 既知のライセンスはありません
- バージョン: 1.0.0
- 分割:
| スプリット | 例 |
|---|---|
'test' | 10000 |
'train' | 1999998 |
- 特徴：
{
"question": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"answer": {
"dtype": "string",
"id": null,
"_type": "Value"
}
}
多項式__evaluate_comped
次のコマンドを使用して、このデータセットを TFDS にロードします。
ds = tfds.load('huggingface:math_dataset/polynomials__evaluate_composed')
- 説明：
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)
- ライセンス: 既知のライセンスはありません
- バージョン: 1.0.0
- 分割:
| スプリット | 例 |
|---|---|
'test' | 10000 |
'train' | 1999998 |
- 特徴：
{
"question": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"answer": {
"dtype": "string",
"id": null,
"_type": "Value"
}
}
多項式__expand
次のコマンドを使用して、このデータセットを TFDS にロードします。
ds = tfds.load('huggingface:math_dataset/polynomials__expand')
- 説明：
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)
- ライセンス: 既知のライセンスはありません
- バージョン: 1.0.0
- 分割:
| スプリット | 例 |
|---|---|
'test' | 10000 |
'train' | 1999998 |
- 特徴：
{
"question": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"answer": {
"dtype": "string",
"id": null,
"_type": "Value"
}
}
多項式__simplify_power
次のコマンドを使用して、このデータセットを TFDS にロードします。
ds = tfds.load('huggingface:math_dataset/polynomials__simplify_power')
- 説明：
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)
- ライセンス: 既知のライセンスはありません
- バージョン: 1.0.0
- 分割:
| スプリット | 例 |
|---|---|
'test' | 10000 |
'train' | 1999998 |
- 特徴：
{
"question": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"answer": {
"dtype": "string",
"id": null,
"_type": "Value"
}
}
確率__swr_p_level_set
次のコマンドを使用して、このデータセットを TFDS にロードします。
ds = tfds.load('huggingface:math_dataset/probability__swr_p_level_set')
- 説明：
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)
- ライセンス: 既知のライセンスはありません
- バージョン: 1.0.0
- 分割:
| スプリット | 例 |
|---|---|
'test' | 10000 |
'train' | 1999998 |
- 特徴：
{
"question": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"answer": {
"dtype": "string",
"id": null,
"_type": "Value"
}
}
確率__swr_p_sequence
次のコマンドを使用して、このデータセットを TFDS にロードします。
ds = tfds.load('huggingface:math_dataset/probability__swr_p_sequence')
- 説明：
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)
- ライセンス: 既知のライセンスはありません
- バージョン: 1.0.0
- 分割:
| スプリット | 例 |
|---|---|
'test' | 10000 |
'train' | 1999998 |
- 特徴：
{
"question": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"answer": {
"dtype": "string",
"id": null,
"_type": "Value"
}
}