OALL/details_deepseek-ai__DeepSeek-R1-Distill-Llama-8B
收藏Hugging Face2025-02-01 更新2025-02-15 收录
下载链接：
https://hf-mirror.com/datasets/OALL/details_deepseek-ai__DeepSeek-R1-Distill-Llama-8B
下载链接
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资源简介：
该数据集是在对模型[deepseek-ai/DeepSeek-R1-Distill-Llama-8B](https://huggingface.co/deepseek-ai/DeepSeek-R1-Distill-Llama-8B)进行评估运行时自动创建的。数据集由136个配置组成，每个配置对应一个评估任务。数据集是从1次运行中创建的。每次运行都可以在配置的特定分割中找到，分割名称使用运行的timestamp命名。"train"分割总是指向最新的结果。还有一个额外的配置"results"存储所有运行的汇总结果。要加载运行的详细信息，可以使用以下Python代码示例：python
from datasets import load_dataset
data = load_dataset("OALL/details_deepseek-ai__DeepSeek-R1-Distill-Llama-8B", "lighteval_xstory_cloze_ar_0_2025_02_01T00_23_41_165779_parquet", split="train")
Dataset automatically created during the evaluation run of model [deepseek-ai/DeepSeek-R1-Distill-Llama-8B](https://huggingface.co/deepseek-ai/DeepSeek-R1-Distill-Llama-8B). The dataset is composed of 136 configurations, each one corresponding to one of the evaluated tasks. The dataset has been created from 1 run(s). Each run can be found as a specific split in each configuration, the split being named using the timestamp of the run. The "train" split is always pointing to the latest results. An additional configuration "results" stores all the aggregated results of the run. To load the details from a run, you can for instance do the following: python
from datasets import load_dataset
data = load_dataset("OALL/details_deepseek-ai__DeepSeek-R1-Distill-Llama-8B", "lighteval_xstory_cloze_ar_0_2025_02_01T00_23_41_165779_parquet", split="train")
提供机构：
OALL
