datasets
Training and evaluation data, with the modality, task and licence stated up front. Listed live from the Hugging Face Hub.
meetingbank
Overview
MeetingBank, a benchmark dataset created from the city councils of 6 major U.S. cities to supplement existing datasets. It contains 1,366 meetings with over 3,579 hours of video, as well as transcripts, PDF documents of meeting minutes, agenda, and other metadata. On average, a council meeting is 2.6 hours long and its transcript contains over 28k tokens, making it a valuable testbed for meeting summarizers and for extracting structure from meeting videos. The datasets… See the full description on the dataset page: https://huggingface.co/datasets/huuuyeah/meetingbank.SportsMetrics
SportsMetrics
Benchmark data to evaluate numerical reasoning and information fusion of LLMs.
SportsMetrics: Blending Text and Numerical Data to Understand Information Fusion in LLMs Yebowen Hu, Kaiqiang Song, Sangwoo Cho, Xiaoyang Wang, Hassan Foroosh, Dong Yu, Fei Liu In Proceedings of the 62nd Annual Meeting of the Association for Computational Linguistics (ACL'24), Bangkok, Thailand. Arxiv Paper
Usage
from datasets import load_dataset
def get_task(domain… See the full description on the dataset page: https://huggingface.co/datasets/huuuyeah/SportsMetrics.saas-chatbot-v4
SaaS Chatbot V4 Dataset
Multi-industry, multilingual conversational dataset for fine-tuning LLMs as SaaS AI chatbot agents with tool calling.
Stats
Metric
Value
Train
4,043
Test
450
Total messages
64,645
Avg msgs/conv
14.4
Think blocks
29,345 (21% empty)
Tool calls
15,215
Tool responses
15,387
Industries (8)
E-commerce (1,301), Travel (641), Services (504), Food (490), Beauty (478), Healthcare (404), Education (357), Real Estate… See the full description on the dataset page: https://huggingface.co/datasets/huutho13254/saas-chatbot-v4.SportsGenDataset and scripts for sports analyzing tasks proposed in research: When Reasoning Meets Information Aggregation: A Case Study with Sports Narratives Yebowen Hu, Kaiqiang Song, Sangwoo Cho, Xiaoyang Wang, Wenlin Yao, Hassan Foroosh, Dong Yu, Fei Liu Accepted to main conference of EMNLP 2024, Miami, Florida, USA Arxiv Paper
Abstract
Reasoning is most powerful when an LLM accurately aggregates relevant information. We examine the critical role of information aggregation in… See the full description on the dataset page: https://huggingface.co/datasets/huuuyeah/SportsGen.first