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> **We're exploring a new abliteration strategy and used the 9B model as a testbed. The > result turned out well — this is currently the state-of-the-art abliterated 9B model > across all three axes at once: capability retention, output brevity, and refusal > removal.** Three variants are published for different deployment needs — pick the one > that matches your setup. > > **我们在尝试一个新的消融策略,以 9B 模型作为练兵场。效果不错 —— 这是目前 abliterated 9B > 领域在能力保留、输出简洁、拒绝移除三方面同时达到最优的一版。** 下面三个仓分别对应不同 > 的部署场景,按需选择即可。 > **This repo bundles seven GGUF quantizations** of > `bowmanslayer/Qwen3.5-9B-Uncensored`, > for llama.cpp / LM Studio / Ollama / Jan / KoboldCpp. File sizes range from **~4.5 GB > (Q3_K_M)** to **18 GB (BF16)** — pick one row from the table below for your device. > Sister repos: full-precision bf16 in the main repo, vLLM-optimized W4A16 in > `-W4A16`. > > **本仓打包 7 档 GGUF 量化**,源自 > `bowmanslayer/Qwen3.5-9B-Uncensored`, > 适用于 llama.cpp / LM Studio / Ollama / Jan / KoboldCpp。文件从 **~4.5 GB(Q3_K_M)** > 到 **18 GB(BF16)**,按下表挑一档匹配你的设备即可。姐妹仓:主仓是全精度 bf16, > vLLM 用的 W4A16 见 `-W4A16`。 > **Vision note**: this repo is **text-only**. The base model has a vision tower, but > llama.cpp GGUF export of Qwen3.5 vision (`mmproj-*.gguf`) is not included here. For > image understanding, use the bf16 main repo or the W4A16 repo with vLLM. > > **视觉说明**:本仓**仅文字**。基座模型带视觉塔,但本仓未包 `mmproj-*.gguf`。要用 > 视觉能力请用主仓 bf16 或 W4A16 版本 + vLLM。

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