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Training and evaluation data, with the modality, task and licence stated up front. Listed live from the Hugging Face Hub.

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01bart2020 /HR_Attritiontabular1K<n<10K0 likes52 downloads3y agoHugging Face02bartoncolton /several-file-3e055f several-file-3e055f Synthetic products test data: 30 rows in data.csv. All values are randomly generated fictional examples, not real observations, products, or user activity. Intended only for CSV loading and pipeline tests; not suitable for scientific or business conclusions. Columns are sampled independently and do not model real-world correlations. Fields sample_id: random identifier for this generated sample. row_id: sequential row number starting at 1.… See the full description on the dataset page: https://huggingface.co/datasets/bartoncolton/several-file-3e055f.tabularn<1K0 likes31 downloads12d agoHugging Face03electricsheepafrica /Net-barter-terms-of-trade-index-2015-100 Net barter terms of trade index 2015 100 | Africa (World Bank) Size category: n<1K - Formats: csv - Sector: economics_finance - Engineered by Electric Sheep Africa TL;DR This dataset is part of the Electric Sheep Africa catalog on Hugging Face. It is indexed for African data discovery with standardized metadata, loading guidance, provenance notes, and analyst-oriented context. What This Dataset Covers Public datasets help analysts inspect… See the full description on the dataset page: https://huggingface.co/datasets/electricsheepafrica/Net-barter-terms-of-trade-index-2015-100.tabulartabular-classificationn<1K0 likes29 downloads1mo agoHugging Face04michaelthwan /wiki_qa_bart_1000rowtabular1K<n<10K0 likes24 downloads4y agoHugging Face05michaelthwan /wiki_qa_bart_10000rowtabular10K<n<100K1 likes12 downloads4y agoHugging Face06adfa5456 /bartendertabular10K<n<100K0 likes8 downloads2y agoHugging Face07tlam25 /json-output-bart-beertabular1K<n<10K0 likes8 downloads1y agoHugging Face08interneuronai /bank_melli_iran_customer_service_chatbot_bart_dataset Bank Melli Iran Customer Service Chatbot Description: Classify customer inquiries into predefined categories and provide automated responses, improving customer service and reducing response time How to Use Here is how to use this model to classify text into different categories: from transformers import AutoModelForSequenceClassification, AutoTokenizer model_name = "interneuronai/bank_melli_iran_customer_service_chatbot_bart" model =… See the full description on the dataset page: https://huggingface.co/datasets/interneuronai/bank_melli_iran_customer_service_chatbot_bart_dataset.tabular1K<n<10K1 likes7 downloads2y agoHugging Face09BartenderXD /MVRLT MVRLT tabularimage-to-3dn<1K0 likes5 downloads1y agoHugging Face

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