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--- |
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language: |
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- zh |
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base_model: |
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- Seikaijyu/RWKV6-3B-v2.1-Aphrodite-yandere-chat |
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tags: |
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- quantization |
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quantized_by: btaskel |
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--- |
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From Seikaijyu/RWKV6-3B-v2.1-Aphrodite-yandere-chat: |
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https://huggingface.co/Seikaijyu/RWKV6-3B-v2.1-Aphrodite-yandere-chat |
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Based on my experience, Q4_K_S and Q4_K_M are usually the balance points between model size, quantization, and speed. |
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In some benchmarks, selecting a large-parameter low-quantization LLM tends to perform better than a small-parameter high-quantization LLM. |
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根据我的经验，通常Q4_K_S、Q4_K_M是模型尺寸/量化/速度的平衡点 |
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在某些基准测试中，选择大参数低量化模型往往比选择小参数高量化模型表现更好。 |
