btaskel/ChenkinNoob-XL-V0.2-GGUF

From civitai/fannon: https://civitai.com/models/2167995/chenkin-noob-xl-ckxl

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，选择大参数高量化模型往往比选择小参数低量化模型表现更好。