הפניות:
אלגברה__לינארית_1ד
השתמש בפקודה הבאה כדי לטעון מערך נתונים זה ב-TFDS:
ds = tfds.load('huggingface:math_dataset/algebra__linear_1d')
- תיאור :
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)
- רישיון : אין רישיון ידוע
- גרסה : 1.0.0
- פיצולים :
| לְפַצֵל | דוגמאות |
|---|---|
'test' | 10000 |
'train' | 1999998 |
- מאפיינים :
{
"question": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"answer": {
"dtype": "string",
"id": null,
"_type": "Value"
}
}
אלגברה__לינארית_1d_קומפוזיט
השתמש בפקודה הבאה כדי לטעון מערך נתונים זה ב-TFDS:
ds = tfds.load('huggingface:math_dataset/algebra__linear_1d_composed')
- תיאור :
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)
- רישיון : אין רישיון ידוע
- גרסה : 1.0.0
- פיצולים :
| לְפַצֵל | דוגמאות |
|---|---|
'test' | 10000 |
'train' | 1999998 |
- מאפיינים :
{
"question": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"answer": {
"dtype": "string",
"id": null,
"_type": "Value"
}
}
אלגברה__לינארית_2ד
השתמש בפקודה הבאה כדי לטעון מערך נתונים זה ב-TFDS:
ds = tfds.load('huggingface:math_dataset/algebra__linear_2d')
- תיאור :
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)
- רישיון : אין רישיון ידוע
- גרסה : 1.0.0
- פיצולים :
| לְפַצֵל | דוגמאות |
|---|---|
'test' | 10000 |
'train' | 1999998 |
- מאפיינים :
{
"question": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"answer": {
"dtype": "string",
"id": null,
"_type": "Value"
}
}
אלגברה__לינארית_2d_קומפוזיט
השתמש בפקודה הבאה כדי לטעון מערך נתונים זה ב-TFDS:
ds = tfds.load('huggingface:math_dataset/algebra__linear_2d_composed')
- תיאור :
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)
- רישיון : אין רישיון ידוע
- גרסה : 1.0.0
- פיצולים :
| לְפַצֵל | דוגמאות |
|---|---|
'test' | 10000 |
'train' | 1999998 |
- מאפיינים :
{
"question": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"answer": {
"dtype": "string",
"id": null,
"_type": "Value"
}
}
אלגברה__פולינום_שורשים
השתמש בפקודה הבאה כדי לטעון מערך נתונים זה ב-TFDS:
ds = tfds.load('huggingface:math_dataset/algebra__polynomial_roots')
- תיאור :
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)
- רישיון : אין רישיון ידוע
- גרסה : 1.0.0
- פיצולים :
| לְפַצֵל | דוגמאות |
|---|---|
'test' | 10000 |
'train' | 1999998 |
- מאפיינים :
{
"question": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"answer": {
"dtype": "string",
"id": null,
"_type": "Value"
}
}
אלגברה__פולינום_שורשים_מורכבים
השתמש בפקודה הבאה כדי לטעון מערך נתונים זה ב-TFDS:
ds = tfds.load('huggingface:math_dataset/algebra__polynomial_roots_composed')
- תיאור :
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)
- רישיון : אין רישיון ידוע
- גרסה : 1.0.0
- פיצולים :
| לְפַצֵל | דוגמאות |
|---|---|
'test' | 10000 |
'train' | 1999998 |
- מאפיינים :
{
"question": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"answer": {
"dtype": "string",
"id": null,
"_type": "Value"
}
}
אלגברה__sequence_next_term
השתמש בפקודה הבאה כדי לטעון מערך נתונים זה ב-TFDS:
ds = tfds.load('huggingface:math_dataset/algebra__sequence_next_term')
- תיאור :
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)
- רישיון : אין רישיון ידוע
- גרסה : 1.0.0
- פיצולים :
| לְפַצֵל | דוגמאות |
|---|---|
'test' | 10000 |
'train' | 1999998 |
- מאפיינים :
{
"question": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"answer": {
"dtype": "string",
"id": null,
"_type": "Value"
}
}
אלגברה__sequence_nth_term
השתמש בפקודה הבאה כדי לטעון מערך נתונים זה ב-TFDS:
ds = tfds.load('huggingface:math_dataset/algebra__sequence_nth_term')
- תיאור :
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)
- רישיון : אין רישיון ידוע
- גרסה : 1.0.0
- פיצולים :
| לְפַצֵל | דוגמאות |
|---|---|
'test' | 10000 |
'train' | 1999998 |
- מאפיינים :
{
"question": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"answer": {
"dtype": "string",
"id": null,
"_type": "Value"
}
}
arithmetic__add_or_sub
השתמש בפקודה הבאה כדי לטעון מערך נתונים זה ב-TFDS:
ds = tfds.load('huggingface:math_dataset/arithmetic__add_or_sub')
- תיאור :
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)
- רישיון : אין רישיון ידוע
- גרסה : 1.0.0
- פיצולים :
| לְפַצֵל | דוגמאות |
|---|---|
'test' | 10000 |
'train' | 1999998 |
- מאפיינים :
{
"question": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"answer": {
"dtype": "string",
"id": null,
"_type": "Value"
}
}
arithmetic__add_or_sub_in_base
השתמש בפקודה הבאה כדי לטעון מערך נתונים זה ב-TFDS:
ds = tfds.load('huggingface:math_dataset/arithmetic__add_or_sub_in_base')
- תיאור :
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)
- רישיון : אין רישיון ידוע
- גרסה : 1.0.0
- פיצולים :
| לְפַצֵל | דוגמאות |
|---|---|
'test' | 10000 |
'train' | 1999998 |
- מאפיינים :
{
"question": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"answer": {
"dtype": "string",
"id": null,
"_type": "Value"
}
}
arithmetic__add_sub_multiple
השתמש בפקודה הבאה כדי לטעון מערך נתונים זה ב-TFDS:
ds = tfds.load('huggingface:math_dataset/arithmetic__add_sub_multiple')
- תיאור :
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)
- רישיון : אין רישיון ידוע
- גרסה : 1.0.0
- פיצולים :
| לְפַצֵל | דוגמאות |
|---|---|
'test' | 10000 |
'train' | 1999998 |
- מאפיינים :
{
"question": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"answer": {
"dtype": "string",
"id": null,
"_type": "Value"
}
}
אריתמטיקה__div
השתמש בפקודה הבאה כדי לטעון מערך נתונים זה ב-TFDS:
ds = tfds.load('huggingface:math_dataset/arithmetic__div')
- תיאור :
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)
- רישיון : אין רישיון ידוע
- גרסה : 1.0.0
- פיצולים :
| לְפַצֵל | דוגמאות |
|---|---|
'test' | 10000 |
'train' | 1999998 |
- מאפיינים :
{
"question": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"answer": {
"dtype": "string",
"id": null,
"_type": "Value"
}
}
חשבון__מעורב
השתמש בפקודה הבאה כדי לטעון מערך נתונים זה ב-TFDS:
ds = tfds.load('huggingface:math_dataset/arithmetic__mixed')
- תיאור :
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)
- רישיון : אין רישיון ידוע
- גרסה : 1.0.0
- פיצולים :
| לְפַצֵל | דוגמאות |
|---|---|
'test' | 10000 |
'train' | 1999998 |
- מאפיינים :
{
"question": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"answer": {
"dtype": "string",
"id": null,
"_type": "Value"
}
}
אריתמטיקה__מול
השתמש בפקודה הבאה כדי לטעון מערך נתונים זה ב-TFDS:
ds = tfds.load('huggingface:math_dataset/arithmetic__mul')
- תיאור :
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)
- רישיון : אין רישיון ידוע
- גרסה : 1.0.0
- פיצולים :
| לְפַצֵל | דוגמאות |
|---|---|
'test' | 10000 |
'train' | 1999998 |
- מאפיינים :
{
"question": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"answer": {
"dtype": "string",
"id": null,
"_type": "Value"
}
}
arithmetic__mul_div_multiple
השתמש בפקודה הבאה כדי לטעון מערך נתונים זה ב-TFDS:
ds = tfds.load('huggingface:math_dataset/arithmetic__mul_div_multiple')
- תיאור :
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)
- רישיון : אין רישיון ידוע
- גרסה : 1.0.0
- פיצולים :
| לְפַצֵל | דוגמאות |
|---|---|
'test' | 10000 |
'train' | 1999998 |
- מאפיינים :
{
"question": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"answer": {
"dtype": "string",
"id": null,
"_type": "Value"
}
}
אריתמטיקה_השורש_שלמה_הקרוב ביותר
השתמש בפקודה הבאה כדי לטעון מערך נתונים זה ב-TFDS:
ds = tfds.load('huggingface:math_dataset/arithmetic__nearest_integer_root')
- תיאור :
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)
- רישיון : אין רישיון ידוע
- גרסה : 1.0.0
- פיצולים :
| לְפַצֵל | דוגמאות |
|---|---|
'test' | 10000 |
'train' | 1999998 |
- מאפיינים :
{
"question": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"answer": {
"dtype": "string",
"id": null,
"_type": "Value"
}
}
אריתמטיקה__לפשט_סורד
השתמש בפקודה הבאה כדי לטעון מערך נתונים זה ב-TFDS:
ds = tfds.load('huggingface:math_dataset/arithmetic__simplify_surd')
- תיאור :
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)
- רישיון : אין רישיון ידוע
- גרסה : 1.0.0
- פיצולים :
| לְפַצֵל | דוגמאות |
|---|---|
'test' | 10000 |
'train' | 1999998 |
- מאפיינים :
{
"question": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"answer": {
"dtype": "string",
"id": null,
"_type": "Value"
}
}
חשבון__להבדיל
השתמש בפקודה הבאה כדי לטעון מערך נתונים זה ב-TFDS:
ds = tfds.load('huggingface:math_dataset/calculus__differentiate')
- תיאור :
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)
- רישיון : אין רישיון ידוע
- גרסה : 1.0.0
- פיצולים :
| לְפַצֵל | דוגמאות |
|---|---|
'test' | 10000 |
'train' | 1999998 |
- מאפיינים :
{
"question": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"answer": {
"dtype": "string",
"id": null,
"_type": "Value"
}
}
חשבון__להבדיל_מורכב
השתמש בפקודה הבאה כדי לטעון מערך נתונים זה ב-TFDS:
ds = tfds.load('huggingface:math_dataset/calculus__differentiate_composed')
- תיאור :
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)
- רישיון : אין רישיון ידוע
- גרסה : 1.0.0
- פיצולים :
| לְפַצֵל | דוגמאות |
|---|---|
'test' | 10000 |
'train' | 1999998 |
- מאפיינים :
{
"question": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"answer": {
"dtype": "string",
"id": null,
"_type": "Value"
}
}
השוואה__הכי קרוב
השתמש בפקודה הבאה כדי לטעון מערך נתונים זה ב-TFDS:
ds = tfds.load('huggingface:math_dataset/comparison__closest')
- תיאור :
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)
- רישיון : אין רישיון ידוע
- גרסה : 1.0.0
- פיצולים :
| לְפַצֵל | דוגמאות |
|---|---|
'test' | 10000 |
'train' | 1999998 |
- מאפיינים :
{
"question": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"answer": {
"dtype": "string",
"id": null,
"_type": "Value"
}
}
השוואה__הכי קרובה
השתמש בפקודה הבאה כדי לטעון מערך נתונים זה ב-TFDS:
ds = tfds.load('huggingface:math_dataset/comparison__closest_composed')
- תיאור :
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)
- רישיון : אין רישיון ידוע
- גרסה : 1.0.0
- פיצולים :
| לְפַצֵל | דוגמאות |
|---|---|
'test' | 10000 |
'train' | 1999998 |
- מאפיינים :
{
"question": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"answer": {
"dtype": "string",
"id": null,
"_type": "Value"
}
}
השוואה__kth_גדולה ביותר
השתמש בפקודה הבאה כדי לטעון מערך נתונים זה ב-TFDS:
ds = tfds.load('huggingface:math_dataset/comparison__kth_biggest')
- תיאור :
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)
- רישיון : אין רישיון ידוע
- גרסה : 1.0.0
- פיצולים :
| לְפַצֵל | דוגמאות |
|---|---|
'test' | 10000 |
'train' | 1999998 |
- מאפיינים :
{
"question": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"answer": {
"dtype": "string",
"id": null,
"_type": "Value"
}
}
השוואה__kth_גדולה ביותר
השתמש בפקודה הבאה כדי לטעון מערך נתונים זה ב-TFDS:
ds = tfds.load('huggingface:math_dataset/comparison__kth_biggest_composed')
- תיאור :
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)
- רישיון : אין רישיון ידוע
- גרסה : 1.0.0
- פיצולים :
| לְפַצֵל | דוגמאות |
|---|---|
'test' | 10000 |
'train' | 1999998 |
- מאפיינים :
{
"question": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"answer": {
"dtype": "string",
"id": null,
"_type": "Value"
}
}
השוואה__זוג
השתמש בפקודה הבאה כדי לטעון מערך נתונים זה ב-TFDS:
ds = tfds.load('huggingface:math_dataset/comparison__pair')
- תיאור :
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)
- רישיון : אין רישיון ידוע
- גרסה : 1.0.0
- פיצולים :
| לְפַצֵל | דוגמאות |
|---|---|
'test' | 10000 |
'train' | 1999998 |
- מאפיינים :
{
"question": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"answer": {
"dtype": "string",
"id": null,
"_type": "Value"
}
}
השוואה__זוג_מורכב
השתמש בפקודה הבאה כדי לטעון מערך נתונים זה ב-TFDS:
ds = tfds.load('huggingface:math_dataset/comparison__pair_composed')
- תיאור :
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)
- רישיון : אין רישיון ידוע
- גרסה : 1.0.0
- פיצולים :
| לְפַצֵל | דוגמאות |
|---|---|
'test' | 10000 |
'train' | 1999998 |
- מאפיינים :
{
"question": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"answer": {
"dtype": "string",
"id": null,
"_type": "Value"
}
}
השוואה__מיון
השתמש בפקודה הבאה כדי לטעון מערך נתונים זה ב-TFDS:
ds = tfds.load('huggingface:math_dataset/comparison__sort')
- תיאור :
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)
- רישיון : אין רישיון ידוע
- גרסה : 1.0.0
- פיצולים :
| לְפַצֵל | דוגמאות |
|---|---|
'test' | 10000 |
'train' | 1999998 |
- מאפיינים :
{
"question": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"answer": {
"dtype": "string",
"id": null,
"_type": "Value"
}
}
השוואה__מיון_מורכב
השתמש בפקודה הבאה כדי לטעון מערך נתונים זה ב-TFDS:
ds = tfds.load('huggingface:math_dataset/comparison__sort_composed')
- תיאור :
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)
- רישיון : אין רישיון ידוע
- גרסה : 1.0.0
- פיצולים :
| לְפַצֵל | דוגמאות |
|---|---|
'test' | 10000 |
'train' | 1999998 |
- מאפיינים :
{
"question": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"answer": {
"dtype": "string",
"id": null,
"_type": "Value"
}
}
המרה_מדידה
השתמש בפקודה הבאה כדי לטעון מערך נתונים זה ב-TFDS:
ds = tfds.load('huggingface:math_dataset/measurement__conversion')
- תיאור :
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)
- רישיון : אין רישיון ידוע
- גרסה : 1.0.0
- פיצולים :
| לְפַצֵל | דוגמאות |
|---|---|
'test' | 10000 |
'train' | 1999998 |
- מאפיינים :
{
"question": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"answer": {
"dtype": "string",
"id": null,
"_type": "Value"
}
}
זמן מדידה
השתמש בפקודה הבאה כדי לטעון מערך נתונים זה ב-TFDS:
ds = tfds.load('huggingface:math_dataset/measurement__time')
- תיאור :
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)
- רישיון : אין רישיון ידוע
- גרסה : 1.0.0
- פיצולים :
| לְפַצֵל | דוגמאות |
|---|---|
'test' | 10000 |
'train' | 1999998 |
- מאפיינים :
{
"question": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"answer": {
"dtype": "string",
"id": null,
"_type": "Value"
}
}
מספרים__המרה_בסיס
השתמש בפקודה הבאה כדי לטעון מערך נתונים זה ב-TFDS:
ds = tfds.load('huggingface:math_dataset/numbers__base_conversion')
- תיאור :
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)
- רישיון : אין רישיון ידוע
- גרסה : 1.0.0
- פיצולים :
| לְפַצֵל | דוגמאות |
|---|---|
'test' | 10000 |
'train' | 1999998 |
- מאפיינים :
{
"question": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"answer": {
"dtype": "string",
"id": null,
"_type": "Value"
}
}
numbers__div_remainder
השתמש בפקודה הבאה כדי לטעון מערך נתונים זה ב-TFDS:
ds = tfds.load('huggingface:math_dataset/numbers__div_remainder')
- תיאור :
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)
- רישיון : אין רישיון ידוע
- גרסה : 1.0.0
- פיצולים :
| לְפַצֵל | דוגמאות |
|---|---|
'test' | 10000 |
'train' | 1999998 |
- מאפיינים :
{
"question": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"answer": {
"dtype": "string",
"id": null,
"_type": "Value"
}
}
מספרים__div_remainder_composed
השתמש בפקודה הבאה כדי לטעון מערך נתונים זה ב-TFDS:
ds = tfds.load('huggingface:math_dataset/numbers__div_remainder_composed')
- תיאור :
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)
- רישיון : אין רישיון ידוע
- גרסה : 1.0.0
- פיצולים :
| לְפַצֵל | דוגמאות |
|---|---|
'test' | 10000 |
'train' | 1999998 |
- מאפיינים :
{
"question": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"answer": {
"dtype": "string",
"id": null,
"_type": "Value"
}
}
מספרים__gcd
השתמש בפקודה הבאה כדי לטעון מערך נתונים זה ב-TFDS:
ds = tfds.load('huggingface:math_dataset/numbers__gcd')
- תיאור :
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)
- רישיון : אין רישיון ידוע
- גרסה : 1.0.0
- פיצולים :
| לְפַצֵל | דוגמאות |
|---|---|
'test' | 10000 |
'train' | 1999998 |
- מאפיינים :
{
"question": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"answer": {
"dtype": "string",
"id": null,
"_type": "Value"
}
}
numbers__gcd_composed
השתמש בפקודה הבאה כדי לטעון מערך נתונים זה ב-TFDS:
ds = tfds.load('huggingface:math_dataset/numbers__gcd_composed')
- תיאור :
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)
- רישיון : אין רישיון ידוע
- גרסה : 1.0.0
- פיצולים :
| לְפַצֵל | דוגמאות |
|---|---|
'test' | 10000 |
'train' | 1999998 |
- מאפיינים :
{
"question": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"answer": {
"dtype": "string",
"id": null,
"_type": "Value"
}
}
מספרים__הוא_גורם
השתמש בפקודה הבאה כדי לטעון מערך נתונים זה ב-TFDS:
ds = tfds.load('huggingface:math_dataset/numbers__is_factor')
- תיאור :
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)
- רישיון : אין רישיון ידוע
- גרסה : 1.0.0
- פיצולים :
| לְפַצֵל | דוגמאות |
|---|---|
'test' | 10000 |
'train' | 1999998 |
- מאפיינים :
{
"question": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"answer": {
"dtype": "string",
"id": null,
"_type": "Value"
}
}
מספרים__הוא_גורם_מורכב
השתמש בפקודה הבאה כדי לטעון מערך נתונים זה ב-TFDS:
ds = tfds.load('huggingface:math_dataset/numbers__is_factor_composed')
- תיאור :
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)
- רישיון : אין רישיון ידוע
- גרסה : 1.0.0
- פיצולים :
| לְפַצֵל | דוגמאות |
|---|---|
'test' | 10000 |
'train' | 1999998 |
- מאפיינים :
{
"question": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"answer": {
"dtype": "string",
"id": null,
"_type": "Value"
}
}
מספרים__הוא_ראשוני
השתמש בפקודה הבאה כדי לטעון מערך נתונים זה ב-TFDS:
ds = tfds.load('huggingface:math_dataset/numbers__is_prime')
- תיאור :
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)
- רישיון : אין רישיון ידוע
- גרסה : 1.0.0
- פיצולים :
| לְפַצֵל | דוגמאות |
|---|---|
'test' | 10000 |
'train' | 1999998 |
- מאפיינים :
{
"question": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"answer": {
"dtype": "string",
"id": null,
"_type": "Value"
}
}
מספרים__מורכבים_ראשוניים
השתמש בפקודה הבאה כדי לטעון מערך נתונים זה ב-TFDS:
ds = tfds.load('huggingface:math_dataset/numbers__is_prime_composed')
- תיאור :
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)
- רישיון : אין רישיון ידוע
- גרסה : 1.0.0
- פיצולים :
| לְפַצֵל | דוגמאות |
|---|---|
'test' | 10000 |
'train' | 1999998 |
- מאפיינים :
{
"question": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"answer": {
"dtype": "string",
"id": null,
"_type": "Value"
}
}
מספרים__lcm
השתמש בפקודה הבאה כדי לטעון מערך נתונים זה ב-TFDS:
ds = tfds.load('huggingface:math_dataset/numbers__lcm')
- תיאור :
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)
- רישיון : אין רישיון ידוע
- גרסה : 1.0.0
- פיצולים :
| לְפַצֵל | דוגמאות |
|---|---|
'test' | 10000 |
'train' | 1999998 |
- מאפיינים :
{
"question": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"answer": {
"dtype": "string",
"id": null,
"_type": "Value"
}
}
מספרים__lcm_composed
השתמש בפקודה הבאה כדי לטעון מערך נתונים זה ב-TFDS:
ds = tfds.load('huggingface:math_dataset/numbers__lcm_composed')
- תיאור :
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)
- רישיון : אין רישיון ידוע
- גרסה : 1.0.0
- פיצולים :
| לְפַצֵל | דוגמאות |
|---|---|
'test' | 10000 |
'train' | 1999998 |
- מאפיינים :
{
"question": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"answer": {
"dtype": "string",
"id": null,
"_type": "Value"
}
}
מספרים_רשימת_גורמי_ראשוניים
השתמש בפקודה הבאה כדי לטעון מערך נתונים זה ב-TFDS:
ds = tfds.load('huggingface:math_dataset/numbers__list_prime_factors')
- תיאור :
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)
- רישיון : אין רישיון ידוע
- גרסה : 1.0.0
- פיצולים :
| לְפַצֵל | דוגמאות |
|---|---|
'test' | 10000 |
'train' | 1999998 |
- מאפיינים :
{
"question": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"answer": {
"dtype": "string",
"id": null,
"_type": "Value"
}
}
מספרים__רשימת_גורמים_ראשוניים_מורכבים
השתמש בפקודה הבאה כדי לטעון מערך נתונים זה ב-TFDS:
ds = tfds.load('huggingface:math_dataset/numbers__list_prime_factors_composed')
- תיאור :
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)
- רישיון : אין רישיון ידוע
- גרסה : 1.0.0
- פיצולים :
| לְפַצֵל | דוגמאות |
|---|---|
'test' | 10000 |
'train' | 1999998 |
- מאפיינים :
{
"question": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"answer": {
"dtype": "string",
"id": null,
"_type": "Value"
}
}
מספרים_ערך_מקום
השתמש בפקודה הבאה כדי לטעון מערך נתונים זה ב-TFDS:
ds = tfds.load('huggingface:math_dataset/numbers__place_value')
- תיאור :
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)
- רישיון : אין רישיון ידוע
- גרסה : 1.0.0
- פיצולים :
| לְפַצֵל | דוגמאות |
|---|---|
'test' | 10000 |
'train' | 1999998 |
- מאפיינים :
{
"question": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"answer": {
"dtype": "string",
"id": null,
"_type": "Value"
}
}
מספרים__מקום_ערך_מורכב
השתמש בפקודה הבאה כדי לטעון מערך נתונים זה ב-TFDS:
ds = tfds.load('huggingface:math_dataset/numbers__place_value_composed')
- תיאור :
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)
- רישיון : אין רישיון ידוע
- גרסה : 1.0.0
- פיצולים :
| לְפַצֵל | דוגמאות |
|---|---|
'test' | 10000 |
'train' | 1999998 |
- מאפיינים :
{
"question": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"answer": {
"dtype": "string",
"id": null,
"_type": "Value"
}
}
מספרים__מספר_עגול
השתמש בפקודה הבאה כדי לטעון מערך נתונים זה ב-TFDS:
ds = tfds.load('huggingface:math_dataset/numbers__round_number')
- תיאור :
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)
- רישיון : אין רישיון ידוע
- גרסה : 1.0.0
- פיצולים :
| לְפַצֵל | דוגמאות |
|---|---|
'test' | 10000 |
'train' | 1999998 |
- מאפיינים :
{
"question": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"answer": {
"dtype": "string",
"id": null,
"_type": "Value"
}
}
מספרים__עגול_מספר_מורכב
השתמש בפקודה הבאה כדי לטעון מערך נתונים זה ב-TFDS:
ds = tfds.load('huggingface:math_dataset/numbers__round_number_composed')
- תיאור :
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)
- רישיון : אין רישיון ידוע
- גרסה : 1.0.0
- פיצולים :
| לְפַצֵל | דוגמאות |
|---|---|
'test' | 10000 |
'train' | 1999998 |
- מאפיינים :
{
"question": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"answer": {
"dtype": "string",
"id": null,
"_type": "Value"
}
}
פולינומים__הוסף
השתמש בפקודה הבאה כדי לטעון מערך נתונים זה ב-TFDS:
ds = tfds.load('huggingface:math_dataset/polynomials__add')
- תיאור :
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)
- רישיון : אין רישיון ידוע
- גרסה : 1.0.0
- פיצולים :
| לְפַצֵל | דוגמאות |
|---|---|
'test' | 10000 |
'train' | 1999998 |
- מאפיינים :
{
"question": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"answer": {
"dtype": "string",
"id": null,
"_type": "Value"
}
}
פולינומים__מקדם_שם
השתמש בפקודה הבאה כדי לטעון מערך נתונים זה ב-TFDS:
ds = tfds.load('huggingface:math_dataset/polynomials__coefficient_named')
- תיאור :
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)
- רישיון : אין רישיון ידוע
- גרסה : 1.0.0
- פיצולים :
| לְפַצֵל | דוגמאות |
|---|---|
'test' | 10000 |
'train' | 1999998 |
- מאפיינים :
{
"question": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"answer": {
"dtype": "string",
"id": null,
"_type": "Value"
}
}
פולינומים__לאסוף
השתמש בפקודה הבאה כדי לטעון מערך נתונים זה ב-TFDS:
ds = tfds.load('huggingface:math_dataset/polynomials__collect')
- תיאור :
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)
- רישיון : אין רישיון ידוע
- גרסה : 1.0.0
- פיצולים :
| לְפַצֵל | דוגמאות |
|---|---|
'test' | 10000 |
'train' | 1999998 |
- מאפיינים :
{
"question": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"answer": {
"dtype": "string",
"id": null,
"_type": "Value"
}
}
פולינומים__לחן
השתמש בפקודה הבאה כדי לטעון מערך נתונים זה ב-TFDS:
ds = tfds.load('huggingface:math_dataset/polynomials__compose')
- תיאור :
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)
- רישיון : אין רישיון ידוע
- גרסה : 1.0.0
- פיצולים :
| לְפַצֵל | דוגמאות |
|---|---|
'test' | 10000 |
'train' | 1999998 |
- מאפיינים :
{
"question": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"answer": {
"dtype": "string",
"id": null,
"_type": "Value"
}
}
פולינומים__להעריך
השתמש בפקודה הבאה כדי לטעון מערך נתונים זה ב-TFDS:
ds = tfds.load('huggingface:math_dataset/polynomials__evaluate')
- תיאור :
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)
- רישיון : אין רישיון ידוע
- גרסה : 1.0.0
- פיצולים :
| לְפַצֵל | דוגמאות |
|---|---|
'test' | 10000 |
'train' | 1999998 |
- מאפיינים :
{
"question": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"answer": {
"dtype": "string",
"id": null,
"_type": "Value"
}
}
פולינומים__הערך_מורכבים
השתמש בפקודה הבאה כדי לטעון מערך נתונים זה ב-TFDS:
ds = tfds.load('huggingface:math_dataset/polynomials__evaluate_composed')
- תיאור :
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)
- רישיון : אין רישיון ידוע
- גרסה : 1.0.0
- פיצולים :
| לְפַצֵל | דוגמאות |
|---|---|
'test' | 10000 |
'train' | 1999998 |
- מאפיינים :
{
"question": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"answer": {
"dtype": "string",
"id": null,
"_type": "Value"
}
}
פולינומים__להרחיב
השתמש בפקודה הבאה כדי לטעון מערך נתונים זה ב-TFDS:
ds = tfds.load('huggingface:math_dataset/polynomials__expand')
- תיאור :
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)
- רישיון : אין רישיון ידוע
- גרסה : 1.0.0
- פיצולים :
| לְפַצֵל | דוגמאות |
|---|---|
'test' | 10000 |
'train' | 1999998 |
- מאפיינים :
{
"question": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"answer": {
"dtype": "string",
"id": null,
"_type": "Value"
}
}
פולינומים__לפשט_כוח
השתמש בפקודה הבאה כדי לטעון מערך נתונים זה ב-TFDS:
ds = tfds.load('huggingface:math_dataset/polynomials__simplify_power')
- תיאור :
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)
- רישיון : אין רישיון ידוע
- גרסה : 1.0.0
- פיצולים :
| לְפַצֵל | דוגמאות |
|---|---|
'test' | 10000 |
'train' | 1999998 |
- מאפיינים :
{
"question": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"answer": {
"dtype": "string",
"id": null,
"_type": "Value"
}
}
probability__swr_p_level_set
השתמש בפקודה הבאה כדי לטעון מערך נתונים זה ב-TFDS:
ds = tfds.load('huggingface:math_dataset/probability__swr_p_level_set')
- תיאור :
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)
- רישיון : אין רישיון ידוע
- גרסה : 1.0.0
- פיצולים :
| לְפַצֵל | דוגמאות |
|---|---|
'test' | 10000 |
'train' | 1999998 |
- מאפיינים :
{
"question": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"answer": {
"dtype": "string",
"id": null,
"_type": "Value"
}
}
probability__swr_p_sequence
השתמש בפקודה הבאה כדי לטעון מערך נתונים זה ב-TFDS:
ds = tfds.load('huggingface:math_dataset/probability__swr_p_sequence')
- תיאור :
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)
- רישיון : אין רישיון ידוע
- גרסה : 1.0.0
- פיצולים :
| לְפַצֵל | דוגמאות |
|---|---|
'test' | 10000 |
'train' | 1999998 |
- מאפיינים :
{
"question": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"answer": {
"dtype": "string",
"id": null,
"_type": "Value"
}
}