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RWKV6-3B-v2.1-Aphrodite-yandere-chat-GGUF – AI Model by btaskel | AlphaNeural AI
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RWKV6-3B-v2.1-Aphrodite-yandere-chat-GGUF
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quantized
Seikaijyu/RWKV6-3B-v2.1-Aphrodite-yandere-chat
conversational
endpoints_compatible
gguf
template
quantization
us
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From Seikaijyu/RWKV6-3B-v2.1-Aphrodite-yandere-chat:
https://huggingface.co/Seikaijyu/RWKV6-3B-v2.1-Aphrodite-yandere-chat
Based on my experience, Q4_K_S and Q4_K_M are usually the balance points between model size, quantization, and speed.
In some benchmarks, selecting a large-parameter high-quantization LLM tends to perform better than a small-parameter low-quantization LLM.
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
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。