fire
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All datasets matching “fire”fire-fusion-wa-1000m
FireFusion WA 1000m
Daily spatio-temporal datacube for wildfire ignition and cause prediction over Washington State, an envelope spanning the Puget lowlands east to the Idaho border. Ten geospatial products spanning terrain, fuels, weather, human activity, lightning, and fire history are aggregated onto a single daily 1km by 1km grid covering every fire season 2003-2020.
Daily fire-season coverage, May 1 - Oct 31 of every year 2003-2020; the window contains every recorded… See the full description on the dataset page: https://huggingface.co/datasets/torq1/fire-fusion-wa-1000m.CoinVE-200K
CoinVE-200K: A Large-Scale High-Quality Dataset for Compositional Instruction-Guided Video Editing
Fuchen Long, Cong Wang, Zitao Gao, Wenhao Zhong, Yu Cheng, Xiaolu Hou
Yan Li, Xiao Cao, Xinlong Sun†, Xi Chen✉, Yu Liu
† Project Leader ✉ Corresponding Author
Smart Creation Platform Department, Online Video BU, Tencent
🌍 Introduction
Instruction-guided video editing has witnessed rapid progress recently, driven by large-scale datasets and… See the full description on the dataset page: https://huggingface.co/datasets/FireCRT/CoinVE-200K.function-calling-eval-dataset-v0The hf dataset contains 2 evaluation datasets
single_turn - The converstaion length for this evaluation dataset is 2. It consists of a user ask followed by a function call by assistant.
multi_turn - The conversation length is variable here but contains a combination of user messages, assistant function calls, assistant messages & tool responses.
Information about the columns
tools - List of functions/tools with specs in JSON format. This is the list of functions the model has to choose from… See the full description on the dataset page: https://huggingface.co/datasets/fireworks-ai/function-calling-eval-dataset-v0.FireSmokeDatasetfirefly-train-1.1M本数据应用于项目：Firefly（流萤）: 中文对话式大语言模型 ，训练后得到的模型firefly-1b4
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我们收集了23个常见的中文数据集，对于每个任务，由人工书写若干种指令模板，保证数据的高质量与丰富度，数据量为115万 。数据分布如下图所示：
每条数据的格式如下，包含任务类型、输入、目标输出：
{
"kind": "ClassicalChinese",
"input": "将下面句子翻译成现代文：\n石中央又生一树，高百余尺，条干偃阴为五色，翠叶如盘，花径尺余，色深碧，蕊深红，异香成烟，著物霏霏。",
"target": "大石的中央长着一棵树，一百多尺高，枝干是彩色的，树叶有盘子那样大，花的直径有一尺宽，花瓣深蓝色，花中飘出奇异的香气笼罩着周围，如烟似雾。"
}
训练数据集的token长度分布如下图所示，绝大部分数据的长度都小于600：
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