mradermacher/Qwen3.8-27B-abliterated-GGUF

🤗 Hugging Face 来源apache-2.0激活 27B373 GBGGUF✓ 22 个校验和今天更新
一条命令提交

在你的模型文件夹旁边运行它。它会制作种子、将文件与 Hugging Face 比对,然后提交。你只需开始做种,并粘贴你账户中的密钥。它只读取你的文件,绝不修改。如果愿意,可以先阅读脚本。

curl -fsSL https://pirateface.co/package.sh | bash -s -- --repo mradermacher/Qwen3.8-27B-abliterated-GGUF ./model-folder
需要做种者 →

About

static quants of https://huggingface.co/wangzhang/Qwen3.8-27B-abliterated

For a convenient overview and download list, visit our model page for this model.

weighted/imatrix quants are available at https://huggingface.co/mradermacher/Qwen3.8-27B-abliterated-i1-GGUF

Usage

If you are unsure how to use GGUF files, refer to one of TheBloke's READMEs for more details, including on how to concatenate multi-part files.

Provided Quants

(sorted by size, not necessarily quality. IQ-quants are often preferable over similar sized non-IQ quants)

Link Type Size/GB Notes
PART 1 PART 2 Q2_K 21.5
PART 1 PART 2 Q3_K_S 24.2
PART 1 PART 2 Q3_K_M 26.7 lower quality
PART 1 PART 2 Q3_K_L 28.8
PART 1 PART 2 IQ4_XS 30.5
PART 1 PART 2 Q4_K_S 31.3 fast, recommended
PART 1 PART 2 Q4_K_M 33.2 fast, recommended
PART 1 PART 2 Q5_K_S 37.5
PART 1 PART 2 Q5_K_M 38.6
PART 1 PART 2 Q6_K 44.3 very good quality
PART 1 PART 2 Q8_0 57.3 fast, best quality

Here is a handy graph by ikawrakow comparing some lower-quality quant types (lower is better):

And here are Artefact2's thoughts on the matter: https://gist.github.com/Artefact2/b5f810600771265fc1e39442288e8ec9

FAQ / Model Request

See https://huggingface.co/mradermacher/model_requests for some answers to questions you might have and/or if you want some other model quantized.

Thanks

I thank my company, nethype GmbH, for letting me use its servers and providing upgrades to my workstation to enable this work in my free time.