Datasets:

carlahq
/

demo-tabular-benchmarks

age int64 17 90	workclass stringclasses 8 values	fnlwgt int64 12.3k 1.49M	education stringclasses 16 values	education-num int64 1 16	marital-status stringclasses 7 values	occupation stringclasses 14 values	relationship stringclasses 6 values	race stringclasses 5 values	sex stringclasses 2 values	capital-gain int64 0 100k	capital-loss int64 0 4.36k	hours-per-week int64 1 99	native-country stringclasses 41 values	class stringclasses 2 values
25	Private	226,802	11th	7	Never-married	Machine-op-inspct	Own-child	Black	Male	0	0	40	United-States	<=50K
38	Private	89,814	HS-grad	9	Married-civ-spouse	Farming-fishing	Husband	White	Male	0	0	50	United-States	<=50K
28	Local-gov	336,951	Assoc-acdm	12	Married-civ-spouse	Protective-serv	Husband	White	Male	0	0	40	United-States	>50K
44	Private	160,323	Some-college	10	Married-civ-spouse	Machine-op-inspct	Husband	Black	Male	7,688	0	40	United-States	>50K
18	null	103,497	Some-college	10	Never-married	null	Own-child	White	Female	0	0	30	United-States	<=50K
34	Private	198,693	10th	6	Never-married	Other-service	Not-in-family	White	Male	0	0	30	United-States	<=50K
29	null	227,026	HS-grad	9	Never-married	null	Unmarried	Black	Male	0	0	40	United-States	<=50K
63	Self-emp-not-inc	104,626	Prof-school	15	Married-civ-spouse	Prof-specialty	Husband	White	Male	3,103	0	32	United-States	>50K
24	Private	369,667	Some-college	10	Never-married	Other-service	Unmarried	White	Female	0	0	40	United-States	<=50K
55	Private	104,996	7th-8th	4	Married-civ-spouse	Craft-repair	Husband	White	Male	0	0	10	United-States	<=50K
65	Private	184,454	HS-grad	9	Married-civ-spouse	Machine-op-inspct	Husband	White	Male	6,418	0	40	United-States	>50K
36	Federal-gov	212,465	Bachelors	13	Married-civ-spouse	Adm-clerical	Husband	White	Male	0	0	40	United-States	<=50K
26	Private	82,091	HS-grad	9	Never-married	Adm-clerical	Not-in-family	White	Female	0	0	39	United-States	<=50K
58	null	299,831	HS-grad	9	Married-civ-spouse	null	Husband	White	Male	0	0	35	United-States	<=50K
48	Private	279,724	HS-grad	9	Married-civ-spouse	Machine-op-inspct	Husband	White	Male	3,103	0	48	United-States	>50K
43	Private	346,189	Masters	14	Married-civ-spouse	Exec-managerial	Husband	White	Male	0	0	50	United-States	>50K
20	State-gov	444,554	Some-college	10	Never-married	Other-service	Own-child	White	Male	0	0	25	United-States	<=50K
43	Private	128,354	HS-grad	9	Married-civ-spouse	Adm-clerical	Wife	White	Female	0	0	30	United-States	<=50K
37	Private	60,548	HS-grad	9	Widowed	Machine-op-inspct	Unmarried	White	Female	0	0	20	United-States	<=50K
40	Private	85,019	Doctorate	16	Married-civ-spouse	Prof-specialty	Husband	Asian-Pac-Islander	Male	0	0	45	null	>50K
34	Private	107,914	Bachelors	13	Married-civ-spouse	Tech-support	Husband	White	Male	0	0	47	United-States	>50K
34	Private	238,588	Some-college	10	Never-married	Other-service	Own-child	Black	Female	0	0	35	United-States	<=50K
72	null	132,015	7th-8th	4	Divorced	null	Not-in-family	White	Female	0	0	6	United-States	<=50K
25	Private	220,931	Bachelors	13	Never-married	Prof-specialty	Not-in-family	White	Male	0	0	43	Peru	<=50K
25	Private	205,947	Bachelors	13	Married-civ-spouse	Prof-specialty	Husband	White	Male	0	0	40	United-States	<=50K
45	Self-emp-not-inc	432,824	HS-grad	9	Married-civ-spouse	Craft-repair	Husband	White	Male	7,298	0	90	United-States	>50K
22	Private	236,427	HS-grad	9	Never-married	Adm-clerical	Own-child	White	Male	0	0	20	United-States	<=50K
23	Private	134,446	HS-grad	9	Separated	Machine-op-inspct	Unmarried	Black	Male	0	0	54	United-States	<=50K
54	Private	99,516	HS-grad	9	Married-civ-spouse	Craft-repair	Husband	White	Male	0	0	35	United-States	<=50K
32	Self-emp-not-inc	109,282	Some-college	10	Never-married	Prof-specialty	Not-in-family	White	Male	0	0	60	United-States	<=50K
46	State-gov	106,444	Some-college	10	Married-civ-spouse	Exec-managerial	Husband	Black	Male	7,688	0	38	United-States	>50K
56	Self-emp-not-inc	186,651	11th	7	Widowed	Other-service	Unmarried	White	Female	0	0	50	United-States	<=50K
24	Self-emp-not-inc	188,274	Bachelors	13	Never-married	Sales	Not-in-family	White	Male	0	0	50	United-States	<=50K
23	Local-gov	258,120	Some-college	10	Married-civ-spouse	Protective-serv	Husband	White	Male	0	0	40	United-States	<=50K
26	Private	43,311	HS-grad	9	Divorced	Exec-managerial	Unmarried	White	Female	0	0	40	United-States	<=50K
65	null	191,846	HS-grad	9	Married-civ-spouse	null	Husband	White	Male	0	0	40	United-States	<=50K
36	Local-gov	403,681	Bachelors	13	Married-civ-spouse	Prof-specialty	Husband	White	Male	0	0	40	United-States	>50K
22	Private	248,446	5th-6th	3	Never-married	Priv-house-serv	Not-in-family	White	Male	0	0	50	Guatemala	<=50K
17	Private	269,430	10th	6	Never-married	Machine-op-inspct	Not-in-family	White	Male	0	0	40	United-States	<=50K
20	Private	257,509	HS-grad	9	Never-married	Craft-repair	Own-child	White	Male	0	0	40	United-States	<=50K
65	Private	136,384	Masters	14	Married-civ-spouse	Prof-specialty	Husband	White	Male	0	0	50	United-States	>50K
44	Self-emp-inc	120,277	Assoc-voc	11	Married-civ-spouse	Sales	Husband	White	Male	0	0	45	United-States	>50K
36	Private	465,326	HS-grad	9	Married-civ-spouse	Farming-fishing	Husband	White	Male	0	0	40	United-States	<=50K
29	Private	103,634	11th	7	Married-civ-spouse	Other-service	Husband	White	Male	0	0	40	United-States	<=50K
20	State-gov	138,371	Some-college	10	Never-married	Farming-fishing	Own-child	White	Male	0	0	32	United-States	<=50K
28	Private	242,832	Assoc-voc	11	Married-civ-spouse	Prof-specialty	Wife	White	Female	0	0	36	United-States	>50K
39	Private	290,208	7th-8th	4	Married-civ-spouse	Craft-repair	Husband	White	Male	0	0	40	Mexico	<=50K
54	Private	186,272	Some-college	10	Married-civ-spouse	Transport-moving	Husband	White	Male	3,908	0	50	United-States	<=50K
52	Private	201,062	11th	7	Separated	Priv-house-serv	Not-in-family	Black	Female	0	0	18	United-States	<=50K
56	Self-emp-inc	131,916	HS-grad	9	Widowed	Exec-managerial	Not-in-family	White	Female	0	0	50	United-States	<=50K
18	Private	54,440	Some-college	10	Never-married	Other-service	Own-child	White	Male	0	0	20	United-States	<=50K
39	Private	280,215	HS-grad	9	Divorced	Handlers-cleaners	Own-child	Black	Male	0	0	40	United-States	<=50K
21	Private	214,399	Some-college	10	Never-married	Other-service	Own-child	White	Female	0	1,721	24	United-States	<=50K
22	Private	54,164	HS-grad	9	Never-married	Other-service	Not-in-family	White	Male	14,084	0	60	United-States	>50K
38	Private	219,446	9th	5	Married-spouse-absent	Exec-managerial	Not-in-family	White	Male	0	0	54	Mexico	<=50K
21	Private	110,677	Some-college	10	Never-married	Adm-clerical	Own-child	White	Female	0	0	40	United-States	<=50K
63	Private	145,985	HS-grad	9	Married-civ-spouse	Craft-repair	Husband	White	Male	0	0	40	United-States	<=50K
34	Local-gov	382,078	Bachelors	13	Married-civ-spouse	Exec-managerial	Husband	White	Male	3,103	0	50	United-States	>50K
42	Self-emp-inc	170,721	HS-grad	9	Married-civ-spouse	Exec-managerial	Husband	White	Male	5,178	0	50	United-States	>50K
33	Private	269,705	HS-grad	9	Married-civ-spouse	Handlers-cleaners	Husband	White	Male	0	0	40	United-States	<=50K
30	Private	101,135	Bachelors	13	Never-married	Exec-managerial	Not-in-family	White	Female	0	0	50	United-States	<=50K
39	Private	118,429	Some-college	10	Divorced	Sales	Not-in-family	White	Male	0	0	40	United-States	<=50K
26	Private	31,208	Masters	14	Never-married	Exec-managerial	Not-in-family	White	Female	0	0	40	United-States	<=50K
33	Private	281,384	HS-grad	9	Never-married	Machine-op-inspct	Own-child	White	Female	0	0	40	United-States	<=50K
47	Local-gov	171,807	HS-grad	9	Divorced	Adm-clerical	Not-in-family	White	Female	0	0	40	United-States	<=50K
41	Private	109,912	Bachelors	13	Never-married	Other-service	Not-in-family	White	Female	0	0	40	null	<=50K
41	Self-emp-inc	445,382	Assoc-acdm	12	Married-civ-spouse	Craft-repair	Husband	White	Male	15,024	0	60	United-States	>50K
19	Private	105,460	Some-college	10	Never-married	Other-service	Own-child	White	Male	0	0	20	United-States	<=50K
46	Private	170,338	HS-grad	9	Separated	Transport-moving	Not-in-family	White	Male	0	0	40	United-States	<=50K
43	Private	102,606	HS-grad	9	Married-civ-spouse	Sales	Husband	White	Male	0	0	48	United-States	<=50K
55	Private	323,887	Some-college	10	Married-civ-spouse	Exec-managerial	Husband	White	Male	15,024	0	45	United-States	>50K
46	Private	175,622	Assoc-voc	11	Married-civ-spouse	Tech-support	Husband	White	Male	0	0	40	United-States	<=50K
30	Private	229,636	HS-grad	9	Married-civ-spouse	Machine-op-inspct	Husband	White	Male	0	0	40	Mexico	<=50K
21	Private	388,946	Some-college	10	Separated	Handlers-cleaners	Not-in-family	White	Female	0	0	40	United-States	<=50K
46	Private	269,034	Some-college	10	Married-civ-spouse	Craft-repair	Husband	Other	Male	0	0	40	Dominican-Republic	<=50K
17	null	165,361	10th	6	Never-married	null	Own-child	White	Male	0	0	40	United-States	<=50K
41	Private	75,012	HS-grad	9	Married-civ-spouse	Machine-op-inspct	Husband	White	Male	0	0	50	United-States	<=50K
69	Self-emp-inc	174,379	HS-grad	9	Married-civ-spouse	Sales	Husband	White	Male	0	0	30	United-States	<=50K
50	Private	312,477	HS-grad	9	Married-civ-spouse	Transport-moving	Husband	White	Male	0	0	40	United-States	<=50K
20	Private	72,055	Some-college	10	Never-married	Adm-clerical	Not-in-family	White	Female	0	0	40	United-States	<=50K
45	Self-emp-inc	67,001	Some-college	10	Married-civ-spouse	Machine-op-inspct	Husband	White	Male	0	0	50	United-States	<=50K
23	Private	213,734	Bachelors	13	Never-married	Exec-managerial	Not-in-family	White	Male	0	0	40	United-States	<=50K
24	Private	83,141	Some-college	10	Separated	Other-service	Not-in-family	White	Male	0	1,876	40	United-States	<=50K
44	Self-emp-inc	223,881	HS-grad	9	Married-civ-spouse	Craft-repair	Husband	White	Male	99,999	0	50	null	>50K
31	Self-emp-not-inc	113,752	Some-college	10	Married-civ-spouse	Craft-repair	Husband	White	Male	0	0	50	United-States	<=50K
43	Private	170,482	HS-grad	9	Separated	Machine-op-inspct	Not-in-family	White	Female	0	0	44	United-States	<=50K
20	Federal-gov	244,689	11th	7	Never-married	Other-service	Own-child	White	Female	0	0	10	United-States	<=50K
55	Private	160,631	HS-grad	9	Married-civ-spouse	Sales	Husband	White	Male	0	0	56	United-States	>50K
24	Federal-gov	228,724	Some-college	10	Never-married	Armed-Forces	Not-in-family	White	Male	0	0	40	United-States	<=50K
41	null	38,434	Masters	14	Married-civ-spouse	null	Wife	White	Female	7,688	0	10	United-States	>50K
59	Private	292,946	Bachelors	13	Never-married	Exec-managerial	Not-in-family	White	Female	0	0	25	United-States	<=50K
49	Federal-gov	77,443	7th-8th	4	Never-married	Other-service	Not-in-family	Black	Male	0	0	20	United-States	<=50K
33	Private	176,410	Masters	14	Married-civ-spouse	Prof-specialty	Wife	White	Female	5,178	0	10	United-States	>50K
59	Federal-gov	98,984	Bachelors	13	Divorced	Adm-clerical	Not-in-family	White	Male	0	0	40	United-States	<=50K
34	Private	198,751	Masters	14	Never-married	Other-service	Not-in-family	Amer-Indian-Eskimo	Male	0	0	40	United-States	<=50K
20	Private	479,296	HS-grad	9	Never-married	Handlers-cleaners	Own-child	White	Male	0	0	40	United-States	<=50K
25	Private	235,218	Bachelors	13	Never-married	Exec-managerial	Own-child	White	Female	0	0	40	United-States	<=50K
49	Private	164,877	10th	6	Married-civ-spouse	Farming-fishing	Husband	White	Male	0	0	40	United-States	<=50K
59	Private	272,087	HS-grad	9	Married-civ-spouse	Transport-moving	Husband	White	Male	0	0	40	United-States	>50K
20	Private	169,699	HS-grad	9	Never-married	Adm-clerical	Not-in-family	White	Female	0	0	40	United-States	<=50K

End of preview. Expand in Data Studio

📊 Carla HQ Tabular Foundation Model Benchmarks

Centralized benchmark repository of canonical tabular datasets curated for Carla HQ and TabICL (In-Context Learning foundation models for tabular data).

Each dataset is hosted as an independent subset/config with native Parquet storage, schema qualities, and synchronized Google Sheets for live spreadsheet experimentation.

🚀 Quickstart (`datasets` library)

Load any benchmark dataset directly using the Hugging Face datasets library:

from datasets import load_dataset

# Load a specific subset (e.g. Bank Marketing)
ds = load_dataset("carlahq/demo-tabular-benchmarks", "bank-marketing")
print(ds["train"])

# Convert directly to pandas DataFrame
df = ds["train"].to_pandas()
print(df.head())

📂 Available Datasets & Subsets

Subset / Config	Dataset Name	Domain	Task Type	Rows	Features	Google Sheet
`adult`	Adult	Operations & Analytics	`binary_classification`	48,842	14	Google Sheet
`amazon-employee-access`	Amazon Employee Access	Finance & Banking	`binary_classification`	32,769	9	Google Sheet
`bank-marketing`	Bank Marketing	Finance & Banking	`binary_classification`	45,211	16	Google Sheet
`breast-w`	Breast W	Healthcare & Life Sciences	`binary_classification`	699	9	Google Sheet
`compas-two-years`	Compas Two Years	Operations & Analytics	`binary_classification`	5,278	13	Google Sheet
`credit-g`	Credit G	Finance & Banking	`binary_classification`	1,000	20	Google Sheet
`diabetes`	Diabetes	Healthcare & Life Sciences	`binary_classification`	768	8	Google Sheet
`employee-salaries`	Employee Salaries	Operations & Analytics	`regression`	9,228	12	Google Sheet
`house-sales`	House Sales	Commerce & Industry	`regression`	21,613	20	Google Sheet
`houses`	Houses	Operations & Analytics	`regression`	20,640	8	Google Sheet
`monks-problems-2`	Monks Problems 2	Operations & Analytics	`binary_classification`	601	6	Google Sheet
`phoneme`	Phoneme	Finance & Banking	`binary_classification`	5,404	5	Google Sheet
`spambase`	Spambase	Finance & Banking	`binary_classification`	4,601	57	Google Sheet

⚡ Integration with Carla Foundation Models

Web Platform: carlahq.eu
Extension: In-browser TabICL extension running zero-server in-context learning directly inside Google Sheets.
Source Code: soda-inria/nanotabicl

Downloads last month: 100

📊 Carla HQ Tabular Foundation Model Benchmarks

🚀 Quickstart (datasets library)

📂 Available Datasets & Subsets

⚡ Integration with Carla Foundation Models

🚀 Quickstart (`datasets` library)