Mitakihara2-DeepSeek-V4-Pro

**[Click here to support our open-source dataset and model releases - help us speed up our release schedule!](https://huggingface.co/spaces/sequelbox/SupportOpenSource)** Mitakihara 2 is an agentic coding dataset focused on MLOps and AI development, testing the limits of DeepSeek-V4-Pro's agentic skills: - Questions prioritize real-world, challenging agentic coding tasks in AI development, research, deployment, interpretability, operation and experimentation. **The primary purpose of the Mitakihara dataset series is to accelerate and decentralize AI development.** - Areas of focus include training and finetuning models, agentic inference, architecture and pipelines, interpretability and evaluation, math, transformers, CUDA, computer science, multi-agent interaction and simulation, experimentation, data engineering, distributed computing, cognition and meta-learning, complex systems, knowledge management, general creativity, and more! - 17k all-new synthetic agentic prompts utilize a variety of personas, experience levels, and styles of communication to maximize real-world flexibility and usability; 5.7k selected prompts from [sequelbox/Mitakihara-DeepSeek-R1-0528](https://huggingface.co/datasets/sequelbox/Mitakihara-DeepSeek-R1-0528) supplement these with additional queries related to AI. - Responses demonstrate the agentic coding capabilities of DeepSeek's V4 Pro model in thinking mode, with an emphasis on maximizing helpfulness to AI development and orchestration. **The dataset responses are presented without alteration;** the Mitakihara 2 dataset strives to accurately represent the V4 Pro model. Potential issues may include inaccurate answers and infinite thought loops. Mitakihara 2 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. Free the machines.