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Update README.md
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README.md
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@@ -32,6 +32,8 @@ As of this writing, with [open-llm-leaderboard](https://huggingface.co/open-llm-
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Wernicke and Vimarckoso both inherit very strong reasoning, and hence high GPQA and MUSR scores, from [EVA-UNIT-01/EVA-Qwen2.5-14B-v0.2](https://huggingface.co/EVA-UNIT-01/EVA-Qwen2.5-14B-v0.2). Prose quality gets a boost from models blended in [Qwenvergence-14B-v6-Prose](https://huggingface.co/Qwenvergence-14B-v6-Prose), and instruction following gets healed after the merges thanks to LoRAs based on [huihui-ai/Qwen2.5-14B-Instruct-abliterated-v2](https://huggingface.co/huihui-ai/Qwen2.5-14B-Instruct-abliterated-v2).
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---
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### Configuration
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Wernicke and Vimarckoso both inherit very strong reasoning, and hence high GPQA and MUSR scores, from [EVA-UNIT-01/EVA-Qwen2.5-14B-v0.2](https://huggingface.co/EVA-UNIT-01/EVA-Qwen2.5-14B-v0.2). Prose quality gets a boost from models blended in [Qwenvergence-14B-v6-Prose](https://huggingface.co/Qwenvergence-14B-v6-Prose), and instruction following gets healed after the merges thanks to LoRAs based on [huihui-ai/Qwen2.5-14B-Instruct-abliterated-v2](https://huggingface.co/huihui-ai/Qwen2.5-14B-Instruct-abliterated-v2).
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Thank you, @mradermacher, @Sangto, and @MaziyarPanahi for the [GGUFs](https://huggingface.co/models?other=base_model:quantized:sometimesanotion/Qwen2.5-14B-Vimarckoso-v3). Anyone who needs to use them with Ollama can use the same modelfile as any Qwen2.5 14B Instruct model. I recommend a temperature of 0.8.
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---
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### Configuration
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