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@@ -28,6 +28,7 @@ We focus on practical questions: how far can small-to-mid-scale models (7B–13B
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  ### 🚨 [Taipei 3.1](https://huggingface.co/tripplet-research/taipei-3.1)
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  ### 🎨 [Majuli 3.1](https://huggingface.co/tripplet-research/majuli3.1)
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  ### 🧠 [Suzhou 3.1](https://huggingface.co/tripplet-research/suzhou3.1)
 
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  An 8.95B SLERP merge combining agent/tool-use capabilities with a broad general-purpose base. Built on the Qwen3.5 architecture with mixed linear + full attention layers, 262K context window, and support for 29+ languages.
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  ### 🚨 [Taipei 3.1](https://huggingface.co/tripplet-research/taipei-3.1)
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  ### 🎨 [Majuli 3.1](https://huggingface.co/tripplet-research/majuli3.1)
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  ### 🧠 [Suzhou 3.1](https://huggingface.co/tripplet-research/suzhou3.1)
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+ ### 🤮 [Synthara Legacy](https://huggingface.co/tripplet-research/synthara-legacy)
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  An 8.95B SLERP merge combining agent/tool-use capabilities with a broad general-purpose base. Built on the Qwen3.5 architecture with mixed linear + full attention layers, 262K context window, and support for 29+ languages.
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