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  • 1
    Ling-V2

    Ling-V2

    Ling-V2 is a MoE LLM provided and open-sourced by InclusionAI

    ...It introduces highly sparse architectures where only a fraction of the model’s parameters are activated per input token, enabling models like Ling-mini-2.0 to achieve reasoning and instruction-following capabilities on par with much larger dense models while remaining significantly more computationally efficient. Trained on more than 20 trillion tokens of high-quality data and enhanced through multi-stage supervised fine-tuning and reinforcement learning, Ling-V2’s models demonstrate strong general reasoning, mathematical problem-solving, coding understanding, and knowledge-intensive task performance.
    Downloads: 0 This Week
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  • 2
    BEVFormer

    BEVFormer

    Implementation of BEVFormer, a camera-only framework

    ...Our approach achieves the new state-of-the-art 56.9\% in terms of NDS metric on the nuScenes \texttt{test} set, which is 9.0 points higher than previous best arts and on par with the performance of LiDAR-based baseline.
    Downloads: 0 This Week
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  • 3
    DeepSeek-V3.2-Speciale

    DeepSeek-V3.2-Speciale

    High-compute ultra-reasoning model surpassing model surpassing GPT-5

    DeepSeek-V3.2-Speciale is the high-compute, ultra-reasoning variant of DeepSeek-V3.2, designed specifically to push the boundaries of mathematical, logical, and algorithmic intelligence. It builds on the DeepSeek Sparse Attention (DSA) framework, delivering dramatically improved long-context efficiency while preserving full model quality. Unlike the standard version, Speciale is tuned exclusively for deep reasoning and therefore does not support tool-calling, focusing its full capacity on...
    Downloads: 0 This Week
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