Deepseek Ai Deepseek R1 Distill Qwen 14b Hugging Face Deepseek developed and released the deepseek r1 distill qwen 14b model, a distilled version of the qwen 14b language model. this variant represents the largest and most powerful model in the deepseek r1 distill series, fine tuned for high performance text generation, dialogue optimization, and advanced reasoning tasks. This model is a multilingual fine tuned version of deepseek ai deepseek r1 distill qwen 14b. other fine tuned versions of this model can be found in our collection, here . this model was trained was trained using our lightblue reasoning multilingual r1 llama 70b train dataset for ~10 minutes on the 8 x l20 instance ( ecs.gn8is 8x.32xlarge ) on.
Deepseek Ai Deepseek R1 Distill Qwen 14b Hugging Face Add files using upload large folder tool 3 months ago; model 00002 of 000004.safetensors. safe. Deepseek r1 distill qwen 14b代表了ai推理模型的重大进步，展示了强化学习在不需要监督微调的情况下实现高性能的能力。 这个模型是deepseek r1的一个迭代版本，以其在涉及数学、编码和推理任务中匹敌甚至超越openai模型的能力而脱颖而出。 值得注意的是，经过提炼的版本deepseek r1 distill qwen 32b为密集模型设定了新的基准，超越了其前身。 deepseek r1 distill qwen 14b代表了ai推理模型的重大进步，展示了强化学习在不需要监督微调的情况下实现高性能的能力。 这个模型是deepseek r1的一个迭代版本，以其在涉及数学、编码和推理任务中匹敌甚至超越openai模型的能力而脱颖而出。. 本文详细介绍了在 2025 年进行 deepseek r1 distill qwen 14b 模型基于 vllm 的部署过程。 从环境准备开始，包括硬件与软件环境要求，如特定的操作系统、gpu 型号、python 版本、cuda 及 pytorch 版本等，指导读者完成基础环境搭建。. To support the research community, we have open sourced deepseek r1 zero, deepseek r1, and six dense models distilled from deepseek r1 based on llama and qwen. deepseek r1 distill qwen 32b outperforms openai o1 mini across various benchmarks, achieving new state of the art results for dense models.
Open Llm Leaderboard Deepseek Ai Deepseek R1 Distill Qwen 14b Details 本文详细介绍了在 2025 年进行 deepseek r1 distill qwen 14b 模型基于 vllm 的部署过程。 从环境准备开始，包括硬件与软件环境要求，如特定的操作系统、gpu 型号、python 版本、cuda 及 pytorch 版本等，指导读者完成基础环境搭建。. To support the research community, we have open sourced deepseek r1 zero, deepseek r1, and six dense models distilled from deepseek r1 based on llama and qwen. deepseek r1 distill qwen 32b outperforms openai o1 mini across various benchmarks, achieving new state of the art results for dense models. Automatically scale the number of replicas within min and max based on compute usage. min is always 0 if scale to zero is active. control what type of trigger will cause your endpoint to scale up. a scale up event will be triggered if the average hardware utilisation (%) exceeds this threshold for more than 20 seconds. 目前提供的mindie镜像预置了deepseek r1 distill qwen 14b模型推理脚本，无需再额外下载魔乐仓库承载的模型适配代码，直接新建容器即可。 执行以下启动命令（参考）： 如果您使用的是root用户镜像（例如从ascend hub上取得），并且可以使用特权容器，请使用以下命令启动容器： privileged \ name