five

sequelbox/Raiden-Mini-DeepSeek-V3.2-Speciale

收藏
Hugging Face2025-12-08 更新2025-12-20 收录
下载链接:
https://hf-mirror.com/datasets/sequelbox/Raiden-Mini-DeepSeek-V3.2-Speciale
下载链接
链接失效反馈
官方服务:
资源简介:
--- license: apache-2.0 tags: - raiden - raiden-mini - creative - analytical - reasoning - rational - deepseek - v3.2-speciale - v3.2 - deepseek-v3.2-speciale - 685b language: - en task_categories: - text-generation size_categories: - 1K<n<10K configs: - config_name: default data_files: Raiden_Mini_DS3.2_Speciale.csv - config_name: comparison data_files: Raiden_Mini_Comparative.csv --- **[Click here to support our open-source dataset and model releases!](https://huggingface.co/spaces/sequelbox/SupportOpenSource)** **Raiden-Mini-DeepSeek-V3.2.Speciale** is a dataset containing creative-reasoning and analytic-reasoning responses, testing the limits of [DeepSeek-V3.2.Speciale's](https://huggingface.co/deepseek-ai/DeepSeek-V3.2-Speciale) reasoning skills! This dataset contains: - a default subset of ~8k 'creative_content' and 'analytical_reasoning' prompts from [sequelbox/Raiden-DeepSeek-R1](https://huggingface.co/datasets/sequelbox/Raiden-DeepSeek-R1), with all responses generated by [DeepSeek V3.2 Speciale.](https://huggingface.co/deepseek-ai/DeepSeek-V3.2-Speciale) - provides an unfiltered look into the reasoning skills of DeepSeek V3.2 Speciale. - suitable to complement other reasoning datasets in finetuning. - a comparison subset with the V3.2 Speciale responses alongside responses from V3.2. - allows for a direct comparison between the V3.2 Speciale and V3.2 models, using the same prompts. - some V3.2 responses (~30) have failed automatic quality checks, as a warning for any finetuning use with the V3.2 column. (No V3.2 Speciale responses failed these checks.) **Responses have not been edited at all:** the Raiden-Mini dataset strives to accurately represent V3.2 Speciale and V3.2. Potential issues may include inaccurate answers and infinite thought loops. Raiden is presented as-is to be used at your discretion. Users should consider applying their own sub-filtering and manual examination of the dataset before use in training. Do as you will.
提供机构:
sequelbox
5,000+
优质数据集
54 个
任务类型
进入经典数据集
二维码
社区交流群

面向社区/商业的数据集话题

二维码
科研交流群

面向高校/科研机构的开源数据集话题

数据驱动未来

携手共赢发展

商业合作