Datasets:

starkdv123
/

mnist-numbers-0to10000-128x128

digits stringlengths 1 5	words stringlengths 3 42	value int32 1 10k	length int32 1 5
1009	one thousand nine	1,009	4
969	nine hundred sixty nine	969	3
8146	eight thousand one hundred forty six	8,146	4
6342	six thousand three hundred forty two	6,342	4
2469	two thousand four hundred sixty nine	2,469	4
7151	seven thousand one hundred fifty one	7,151	4
8831	eight thousand eight hundred thirty one	8,831	4
1550	one thousand five hundred fifty	1,550	4
1781	one thousand seven hundred eighty one	1,781	4
7771	seven thousand seven hundred seventy one	7,771	4
348	three hundred forty eight	348	3
3181	three thousand one hundred eighty one	3,181	4
5340	five thousand three hundred forty	5,340	4
3974	three thousand nine hundred seventy four	3,974	4
6551	six thousand five hundred fifty one	6,551	4
6191	six thousand one hundred ninety one	6,191	4
761	seven hundred sixty one	761	3
4090	four thousand ninety	4,090	4
4550	four thousand five hundred fifty	4,550	4
1327	one thousand three hundred twenty seven	1,327	4
3294	three thousand two hundred ninety four	3,294	4
6143	six thousand one hundred forty three	6,143	4
6653	six thousand six hundred fifty three	6,653	4
114	one hundred fourteen	114	3
1076	one thousand seventy six	1,076	4
3711	three thousand seven hundred eleven	3,711	4
2677	two thousand six hundred seventy seven	2,677	4
3658	three thousand six hundred fifty eight	3,658	4
2699	two thousand six hundred ninety nine	2,699	4
6601	six thousand six hundred one	6,601	4
6890	six thousand eight hundred ninety	6,890	4
2365	two thousand three hundred sixty five	2,365	4
6874	six thousand eight hundred seventy four	6,874	4
5805	five thousand eight hundred five	5,805	4
6884	six thousand eight hundred eighty four	6,884	4
9190	nine thousand one hundred ninety	9,190	4
2273	two thousand two hundred seventy three	2,273	4
2969	two thousand nine hundred sixty nine	2,969	4
9083	nine thousand eighty three	9,083	4
8126	eight thousand one hundred twenty six	8,126	4
7728	seven thousand seven hundred twenty eight	7,728	4
3295	three thousand two hundred ninety five	3,295	4
6226	six thousand two hundred twenty six	6,226	4
8775	eight thousand seven hundred seventy five	8,775	4
5550	five thousand five hundred fifty	5,550	4
285	two hundred eighty five	285	3
7336	seven thousand three hundred thirty six	7,336	4
1663	one thousand six hundred sixty three	1,663	4
963	nine hundred sixty three	963	3
8389	eight thousand three hundred eighty nine	8,389	4
5464	five thousand four hundred sixty four	5,464	4
8749	eight thousand seven hundred forty nine	8,749	4
5722	five thousand seven hundred twenty two	5,722	4
6776	six thousand seven hundred seventy six	6,776	4
9694	nine thousand six hundred ninety four	9,694	4
6954	six thousand nine hundred fifty four	6,954	4
6251	six thousand two hundred fifty one	6,251	4
75	seventy five	75	2
6221	six thousand two hundred twenty one	6,221	4
5590	five thousand five hundred ninety	5,590	4
7084	seven thousand eighty four	7,084	4
7203	seven thousand two hundred three	7,203	4
6422	six thousand four hundred twenty two	6,422	4
2615	two thousand six hundred fifteen	2,615	4
780	seven hundred eighty	780	3
8205	eight thousand two hundred five	8,205	4
4187	four thousand one hundred eighty seven	4,187	4
191	one hundred ninety one	191	3
435	four hundred thirty five	435	3
6840	six thousand eight hundred forty	6,840	4
1945	one thousand nine hundred forty five	1,945	4
230	two hundred thirty	230	3
2902	two thousand nine hundred two	2,902	4
8288	eight thousand two hundred eighty eight	8,288	4
1288	one thousand two hundred eighty eight	1,288	4
996	nine hundred ninety six	996	3
6865	six thousand eight hundred sixty five	6,865	4
1354	one thousand three hundred fifty four	1,354	4
6834	six thousand eight hundred thirty four	6,834	4
2180	two thousand one hundred eighty	2,180	4
30	thirty	30	2
6183	six thousand one hundred eighty three	6,183	4
1091	one thousand ninety one	1,091	4
4532	four thousand five hundred thirty two	4,532	4
7739	seven thousand seven hundred thirty nine	7,739	4
8447	eight thousand four hundred forty seven	8,447	4
3616	three thousand six hundred sixteen	3,616	4
9297	nine thousand two hundred ninety seven	9,297	4
5095	five thousand ninety five	5,095	4
3816	three thousand eight hundred sixteen	3,816	4
2904	two thousand nine hundred four	2,904	4
291	two hundred ninety one	291	3
5412	five thousand four hundred twelve	5,412	4
5234	five thousand two hundred thirty four	5,234	4
2616	two thousand six hundred sixteen	2,616	4
4842	four thousand eight hundred forty two	4,842	4
1639	one thousand six hundred thirty nine	1,639	4
4014	four thousand fourteen	4,014	4
1760	one thousand seven hundred sixty	1,760	4
3170	three thousand one hundred seventy	3,170	4

End of preview. Expand in Data Studio

MNIST Numbers 0..10,000 (128×128)

10,000 synthetic grayscale images composed from MNIST digits (black on white), resized to 128×128. Each row corresponds to an integer n ∈ [0, 10,000] and includes:

image: digits tiled left→right with small rotation jitter
digits: e.g., "10000"
words: e.g., "ten thousand" (no "and")
value: integer 0..10,000
length: number of digits (1..5)

Splits

train: 9,000
test: 1,000

Usage

from datasets import load_dataset
DS = load_dataset("starkdv123/mnist-numbers-0to10000-128x128")
ex = DS["train"][0]
ex["image"].show()
print(ex["value"], ex["digits"], " | ", ex["words"])

Notes

Digits are sampled from torchvision.datasets.MNIST(train=True).
Mild rotation jitter (±10°); composed horizontally then resized to square.
Images are file-backed (PNG) to ensure Hub Dataset Viewer compatibility (Parquet auto-conversion).

Downloads last month: 39

Size of downloaded dataset files:

39.5 MB

Size of the auto-converted Parquet files:

39.5 MB

Number of rows:

10,000