datasets
Training and evaluation data, with the modality, task and licence stated up front. Listed live from the Hugging Face Hub.
jev-ai-api-guide-assetsjlw-apikaggle-api-test
kaggle-api-test — dev artifact mirror + CLIFFX visual gallery
Working log for the anchor-decay reconstruction campaign (Kaggle notebook
v9k7 series -> flush here; pulled + hash-audited + mirrored each round).
Status 2026-09-25 (post-CLIFFX): pre-registered stop triggered. Ship
artifact = champion weights 33c735603c9f (weights/model_conv_g112.pt)
deployed stack policy (ROUTER_T 0.4622 / k=2 / TAU 0.70-0.80).
All search arms closed under the re-anchored deployed gate:
0/284… See the full description on the dataset page: https://huggingface.co/datasets/favvnna/kaggle-api-test.jev-api-article-assetsphonkAPIGA_2025mozart-api-demo-pages
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Source Data… See the full description on the dataset page: https://huggingface.co/datasets/DoctorSlimm/mozart-api-demo-pages.apnr-ml-apicarpet-analysis-api
🧵 Macro Carpet Classification Dataset
A high-resolution macro photography dataset consisting of 898 curated carpet images across 6 distinct carpet styles and 3 fiber material compositions, developed for automated quality assessment and authentication research.
📊 Dataset Specifications
Total Images: 898 high-resolution macro photographs
Image Dimensions: 1600 × 1600 pixels
Format: JPEG (.jpg)
Modality: Macro surface photography (01_Makroskopis)… See the full description on the dataset page: https://huggingface.co/datasets/yosedie/carpet-analysis-api.mozart-api
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Source Data… See the full description on the dataset page: https://huggingface.co/datasets/DoctorSlimm/mozart-api.exercise-api
Exercise API — Dataset
Dataset de 104 ejercicios de gimnasio (bilingüe ES/EN) derivado de la
Exercise API. Cada ejercicio incluye grupo muscular,
equipamiento, músculos principal/secundario, instrucciones paso a paso e ilustración
masculina y femenina (208 imágenes en total).
Configuraciones
images — 1 fila por imagen (208). Etiquetas (grupo, equipamiento,
músculos, género) + caption_es/caption_en. Para clasificación de imagen y multimodal
(image-to-text / VQA).… See the full description on the dataset page: https://huggingface.co/datasets/natzx94/exercise-api.prototype-jenga-pickup-shortThis dataset was created using LeRobot.
Dataset Structure
meta/info.json:
{
"codebase_version": "v3.0",
"robot_type": "so101_follower",
"total_episodes": 35,
"total_frames": 14662,
"total_tasks": 1,
"chunks_size": 1000,
"data_files_size_in_mb": 100,
"video_files_size_in_mb": 200,
"fps": 30,
"splits": {
"train": "0:35"
},
"data_path": "data/chunk-{chunk_index:03d}/file-{file_index:03d}.parquet",
"video_path":… See the full description on the dataset page: https://huggingface.co/datasets/apinguen/prototype-jenga-pickup-short.scifi_new_test_api
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This dataset was produced with DataDreamer 🤖💤. The synthetic dataset card can be found here.
prototype-jenga-pickup-data1prototype-jenga-pickup-long-datasetimnet1k_apiary_bee_houseprototype-jenga-pickup-long-2api_test_chartqa_contllama-api-assetsapi_test_chartqa_oriapi_test_chartqa_ansAPISR_Dataset
APISR Training Dataset
Paper (ArXiv) | Code | 🤗 Gradio demo
Introduction
While real-world anime super-resolution (SR) has gained increasing attention in the SR community, existing methods still adopt techniques from the photorealistic
domain. In this paper, we analyze the anime production workflow and rethink how to use characteristics of it for the sake of the real-world anime SR. First, we argue that
video networks and datasets are not necessary for anime
SR due… See the full description on the dataset page: https://huggingface.co/datasets/HikariDawn/APISR_Dataset.prototype-jenga-pickup-long-3News_bcn_sentimentNews on Barcelona en spanish media outlets
prototype-jenga-pickup-dataysda-2026-seminar-yatasks-apimonai-cloud-apiapi-geoagri-vlmApiaVizDatasetsAPI-pics