diff --git a/gallery/index.yaml b/gallery/index.yaml index 68431c423e4c..37f45901c7dc 100644 --- a/gallery/index.yaml +++ b/gallery/index.yaml @@ -23023,3 +23023,33 @@ - filename: Qwen3-Yoyo-V4-42B-A3B-Thinking-TOTAL-RECALL-PKDick-V.i1-Q4_K_M.gguf sha256: 6955283520e3618fe349bb75f135eae740f020d9d7f5ba38503482e5d97f6f59 uri: huggingface://mradermacher/Qwen3-Yoyo-V4-42B-A3B-Thinking-TOTAL-RECALL-PKDick-V-i1-GGUF/Qwen3-Yoyo-V4-42B-A3B-Thinking-TOTAL-RECALL-PKDick-V.i1-Q4_K_M.gguf +- !!merge <<: *llama33 + name: "grovemoe-base-i1" + urls: + - https://huggingface.co/mradermacher/GroveMoE-Base-i1-GGUF + description: | + **GroveMoE-Base** + *Efficient, Sparse Mixture-of-Experts LLM with Adjugate Experts* + + GroveMoE-Base is a 33-billion-parameter sparse Mixture-of-Experts (MoE) language model designed for high efficiency and strong performance. Unlike dense models, only 3.14–3.28 billion parameters are activated per token, drastically reducing computational cost while maintaining high capability. + + **Key Features:** + - **Novel Architecture**: Uses *adjugate experts* to dynamically allocate computation, enabling shared processing and significant FLOP reduction. + - **Efficient Inference**: Achieves high throughput with low latency, ideal for deployment in resource-constrained environments. + - **Based on Qwen3-30B-A3B-Base**: Up-cycled through mid-training and supervised fine-tuning, preserving strong pre-trained knowledge while adding new capabilities. + + **Use Cases:** + Ideal for applications requiring efficient large-scale language understanding and generation—such as chatbots, content creation, and code generation—where speed and resource efficiency are critical. + + **Paper:** [GroveMoE: Towards Efficient and Superior MoE LLMs with Adjugate Experts](https://arxiv.org/abs/2508.07785) + **Model Hub:** [inclusionAI/GroveMoE-Base](https://huggingface.co/inclusionAI/GroveMoE-Base) + **GitHub:** [github.com/inclusionAI/GroveMoE](https://github.com/inclusionAI/GroveMoE) + + *Note: The GGUF quantized versions (e.g., mradermacher/GroveMoE-Base-i1-GGUF) are community-quantized derivatives. The original model is the base model by inclusionAI.* + overrides: + parameters: + model: GroveMoE-Base.i1-Q4_K_M.gguf + files: + - filename: GroveMoE-Base.i1-Q4_K_M.gguf + sha256: 9d7186ba9531bf689c91176468d7a35c0aaac0cd52bd44d4ed8f7654949ef4f4 + uri: huggingface://mradermacher/GroveMoE-Base-i1-GGUF/GroveMoE-Base.i1-Q4_K_M.gguf