datasets
Training and evaluation data, with the modality, task and licence stated up front. Listed live from the Hugging Face Hub.
qwen3_5-a2d-stage1-sft
Qwen3.5 A2D Stage 1 SFT
Curated general supervised fine-tuning corpus for Qwen3.5 text-only A2D BD3LM experiments.
Files
train-*.parquet: canonical training split data (54 shard(s)).
stage1_sft_metadata.json: curation counts and source-level metadata.
metadata.json: duplicate of the stage metadata for quick inspection.
Loading
from datasets import load_dataset
dataset = load_dataset("parquet", data_files={"train": "train-*.parquet"})
Curation Details… See the full description on the dataset page: https://huggingface.co/datasets/shreyvish5678/qwen3_5-a2d-stage1-sft.A2_DatasetThis is the official repository for the training dataset of the paper: Efficient Alignment of Unconditioned Action Prior for Language-conditioned Pick and Place in Clutter. Please download the file and unzip it in the data folder.
A2D2a2d_sentencesa2d1bcf0
Dataset Card for "a2d1bcf0"
More Information needed
SpeechOcean762_for_ConPCOThis preprocess dataset is used for ConPCO: Preserving Phoneme Characteristics For Automatic Pronunciation Assessment Leveraging Contrastive Ordinal Regularization, which is published at IEEE ICASSP 2025.
The dataset has a total size of approximately 12 GB. To facilitate faster downloads, we have compressed the files into ZIP archives. Please unzip the archives after downloading to access the data.
The Gihub repository of ConPCO is at here.
license: cc-by-4.0
africa-nigeria-transport-fare-watch-a2d2cfe6
Transport Fare Watch | Africa (National Bureau of Statistics, Nigeria)
73 rows - 1 Africa country/area - 2025 - source table - Engineered by Electric Sheep Africa
TL;DR
This dataset contains 73 rows from National Bureau of Statistics, Nigeria, covering Transport Fare Watch. It is published as ML-ready Parquet with consistent Hugging Face metadata, source provenance, and analysis-friendly loading examples.
What This Dataset Measures
Transport… See the full description on the dataset page: https://huggingface.co/datasets/electricsheepafrica/africa-nigeria-transport-fare-watch-a2d2cfe6.africa-tunisia-station-climatique-kairouan-sbikha-dgacta-a2d887c6
Station Climatique Kairouan Sbikha Dgacta | Africa (Tunisia Open Data)
6 rows - 1 Africa country/area - 2025 - 1 indicator - Engineered by Electric Sheep Africa
TL;DR
This dataset contains 6 rows from Tunisia Open Data, covering Station Climatique Kairouan Sbikha Dgacta. It is published as ML-ready Parquet with consistent Hugging Face metadata, source provenance, and analysis-friendly loading examples.
What This Dataset Measures
Agriculture… See the full description on the dataset page: https://huggingface.co/datasets/electricsheepafrica/africa-tunisia-station-climatique-kairouan-sbikha-dgacta-a2d887c6.A2D2_gemini-1.5-Flashqwen3_5-a2d-stage2-reasoning
Qwen3.5 A2D Stage 2 Reasoning SFT
Curated reasoning-focused supervised fine-tuning corpus for stage-2 Qwen3.5 text-only A2D BD3LM experiments.
Files
train-*.parquet: canonical training split data (1 shard(s)).
stage2_reasoning_metadata.json: curation counts and source-level metadata.
metadata.json: duplicate of the stage metadata for quick inspection.
Loading
from datasets import load_dataset
dataset = load_dataset("parquet", data_files={"train":… See the full description on the dataset page: https://huggingface.co/datasets/shreyvish5678/qwen3_5-a2d-stage2-reasoning.africa-gambia-gambia-views-conflict-forecasts-a2dd7964
Gambia - VIEWS conflict forecasts | Africa (Gambia official open data)
36 rows - 1 Africa country - 2026-2027 - Repackaged by Electric Sheep Africa
TL;DR
This dataset packages one official CSV resource from Gambia as
ML-ready Parquet. The source file is the provenance boundary; all usable
indicators or tabular columns from the resource stay together in this repo.
About the source
Source: Gambia - VIEWS conflict forecasts
Publisher: Violence &… See the full description on the dataset page: https://huggingface.co/datasets/electricsheepafrica/africa-gambia-gambia-views-conflict-forecasts-a2dd7964.africa-morocco-archive-2024-statistiques-hebdomadaires-des-organismes-de-a2dc12df
Archive 2024 Statistiques Hebdomadaires Des Organismes De | Africa (Morocco Open Data)
37 rows - 1 Africa country/area - time not specified - source table - Engineered by Electric Sheep Africa
TL;DR
This dataset contains 37 rows from Morocco Open Data, covering Archive 2024 Statistiques Hebdomadaires Des Organismes De. It is published as ML-ready Parquet with consistent Hugging Face metadata, source provenance, and analysis-friendly loading examples.… See the full description on the dataset page: https://huggingface.co/datasets/electricsheepafrica/africa-morocco-archive-2024-statistiques-hebdomadaires-des-organismes-de-a2dc12df.africa-chad-chad-trade-a2d4dba1
Chad Trade | Africa (World Bank Group)
3,444 rows - 1 Africa country/area - 1960-2025 - 1 indicator - Engineered by Electric Sheep Africa
TL;DR
This dataset contains 3,444 rows from World Bank Group, covering Chad Trade. It is published as ML-ready Parquet with consistent Hugging Face metadata, source provenance, and analysis-friendly loading examples.
What This Dataset Measures
Economic datasets help analysts examine production, prices, public… See the full description on the dataset page: https://huggingface.co/datasets/electricsheepafrica/africa-chad-chad-trade-a2d4dba1.a2d-sft-dataafrica-eritrea-eritrea-accessibility-indicators-a2dac081
Eritrea - Accessibility Indicators | Africa (Eritrea official open data)
978 rows - 1 Africa country - 2020-2025 - Repackaged by Electric Sheep Africa
TL;DR
This dataset packages one official CSV resource from Eritrea as
ML-ready Parquet. The source file is the provenance boundary; all usable
indicators or tabular columns from the resource stay together in this repo.
About the source
Source: Eritrea - Accessibility Indicators
Publisher: HeiGIT… See the full description on the dataset page: https://huggingface.co/datasets/electricsheepafrica/africa-eritrea-eritrea-accessibility-indicators-a2dac081.fuego-20230225-074209-a2dfb7bild-d4382040-b991-4721-a2df-eb2fd8fed1f2test_import_dataset_from_hub_with_classlabel_c6febf7c-a2d9-46fa-b344-a6e4902d4823dataset_for_job_e27eae04_3a5b_4a8b_b3c7_a2d956f2315etest_import_dataset_from_hub_with_classlabel_3ff4273c-efee-44e8-a2da-ad83233df50ctest_import_dataset_from_hub_with_classlabel_ef0dd316-f8df-4a7c-b8ec-a2d87720f559test_import_dataset_from_hub_with_classlabel_a2d41a08-3c79-4072-ad29-94618063f848test_import_dataset_from_hub_with_classlabel_3ad0fb8b-f849-4596-bb21-a2dcaef41b99a2d_grasp_bottletest_import_dataset_from_hub_with_classlabel_d1872031-a2db-4be6-ad14-be37312fdc81test_import_dataset_from_hub_with_classlabel_4ad4e5f9-c185-4a3f-b430-a2dd46ec6175test_import_dataset_from_hub_with_classlabel_a2df4c3e-e7af-4143-a820-382659529329a2d_lora_test_dataa2d_picking_sim_1202_all_vpa2DWnMcM