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AI モデル 84760

• All-MiniLM-L6-v2-Embedding-GGUF↗

  second-state

• smollm3-sft-unit1↗

  Seif6

• stsb-bert-large↗

  sentence-transformers

• Doge-320M↗

  SmallDoge

  Doge uses Dynamic Mask Attention as sequence transformation and can use Multi-Layer Perceptron or Cross Domain Mixture of Experts as state transformation. Dynamic Mask Attention allows the Transformer to use self-attention during training and state space during inference, and Cross Domain Mixture of Experts can directly inherit the weights of Multi-Layer Perceptron for further training. This model is trained by SmallDoge community, for detailed algorithm and model architecture, paper coming soon, all training details and code are available in the small-doge repository. We build the Doge by doing Per-Training on Smollm-Corpus. If you want to continue pre-training this model, you can find the unconverged checkpoint here. These models has not been fine-tuned for instruction, the instruction model is here.

• JoyAI-Echo-gguf↗

  smthem

• birefnet-lite-512↗

  studioludens

  A 512×512 ONNX re-export of ZhengPeng7/BiRefNet_lite that actually runs in a browser — solving the OOM wall that blocks every 1024×1024 variant from loading in `onnxruntime-web`. Drop it in with `@huggingface/transformers` to get high-quality alpha mattes entirely client-side, with no server round-trip. Used in production by Repper for per-motif matte refinement during foreground extraction. The 1024×1024 ONNX variants — including `onnx-community/BiRefNet_lite-ONNX` — fail in every browser backend we tested:

• Qwen2.5-Omni-3B-MNN↗

  taobao-mnn

• Qwen3-4B-Thinking-2507-MiniMax-M2.1-Distill-GGUF↗

  TeichAI

• TimeLens-7B↗

  TencentARC

• WizardLM-7B-uncensored-GPTQ↗

  TheBloke