中医防治胃癌数据库|中医数据集|胃癌防治数据集
收藏lmarena-ai/arena-hard-auto-v0.1
--- license: apache-2.0 dataset_info: features: - name: question_id dtype: string - name: category dtype: string - name: cluster dtype: string - name: turns list: - name: content dtype: string splits: - name: train num_bytes: 251691 num_examples: 500 download_size: 154022 dataset_size: 251691 configs: - config_name: default data_files: - split: train path: data/train-* --- ## Arena-Hard-Auto **Arena-Hard-Auto-v0.1** ([See Paper](https://arxiv.org/abs/2406.11939)) is an automatic evaluation tool for instruction-tuned LLMs. It contains 500 challenging user queries sourced from Chatbot Arena. We prompt GPT-4-Turbo as judge to compare the models' responses against a baseline model (default: GPT-4-0314). Notably, Arena-Hard-Auto has the highest *correlation* and *separability* to Chatbot Arena among popular open-ended LLM benchmarks ([See Paper](https://arxiv.org/abs/2406.11939)). If you are curious to see how well your model might perform on Chatbot Arena, we recommend trying Arena-Hard-Auto. Please checkout our GitHub repo on how to evaluate models using Arena-Hard-Auto and more information about the benchmark. If you find this dataset useful, feel free to cite us! ``` @article{li2024crowdsourced, title={From Crowdsourced Data to High-Quality Benchmarks: Arena-Hard and BenchBuilder Pipeline}, author={Li, Tianle and Chiang, Wei-Lin and Frick, Evan and Dunlap, Lisa and Wu, Tianhao and Zhu, Banghua and Gonzalez, Joseph E and Stoica, Ion}, journal={arXiv preprint arXiv:2406.11939}, year={2024} } ```
hugging_face 收录
google-10000-english
该数据集包含10,000个最常用的英语单词,按频率排序,来源于Google的万亿词料库的n-gram频率分析。数据集可用于多种应用,如打字训练程序,其中7,000个最常用的英语词汇已覆盖约90%的日常使用。
github 收录
QM9
QM9数据集包含134k个有机小分子化合物的量子化学计算结果,涵盖了12个量子化学性质,如分子能量、电离能、电子亲和能等。
quantum-machine.org 收录
ANC
美国国家语料库(American National Corpus,简称ANC)是一个大规模的电子美国英语语料库,包含多种类型文本及口语数据转录,旨在全面反映美国英语的多样性。其开放部分OANC约有1500万字,涵盖多种文体,且进行了自动标注。
anc.org 收录
UAVDT Dataset
The authors constructed a new UAVDT Dataset focused on complex scenarios with new level challenges. Selected from 10 hours raw videos, about 80, 000 representative frames are fully annotated with bounding boxes as well as up to 14 kinds of attributes (e.g., weather condition, flying altitude, camera view, vehicle category, and occlusion) for three fundamental computer vision tasks: object detection, single object tracking, and multiple object tracking.
datasetninja.com 收录