mradermacher/Huihui-MoE-5B-A1.7B-abliterated-i1-GGUF

---

base_model: huihui-ai/Huihui-MoE-5B-A1.7B-abliterated extragatedprompt: |- Usage Warnings

“Risk of Sensitive or Controversial Outputs“: This model’s safety filtering has been significantly reduced, potentially generating sensitive, controversial, or inappropriate content. Users should exercise caution and rigorously review generated outputs.
“Not Suitable for All Audiences:“ Due to limited content filtering, the model’s outputs may be inappropriate for public settings, underage users, or applications requiring high security.
“Legal and Ethical Responsibilities“: Users must ensure their usage complies with local laws and ethical standards. Generated content may carry legal or ethical risks, and users are solely responsible for any consequences.
“Research and Experimental Use“: It is recommended to use this model for research, testing, or controlled environments, avoiding direct use in production or public-facing commercial applications.
“Monitoring and Review Recommendations“: Users are strongly advised to monitor model outputs in real-time and conduct manual reviews when necessary to prevent the dissemination of inappropriate content.
“No Default Safety Guarantees“: Unlike standard models, this model has not undergone rigorous safety optimization. huihui.ai bears no responsibility for any consequences arising from its use.
language:

• en

library_name: transformers
license: apache-2.0
license_link: https://huggingface.co/Qwen/Qwen3-1.7B/blob/main/LICENSE
mradermacher:
readme_rev: 1
quantized_by: mradermacher
tags:

• moe

---

About

weighted/imatrix quants of https://huggingface.co/huihui-ai/Huihui-MoE-5B-A1.7B-abliterated

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

static quants are available at https://huggingface.co/mradermacher/Huihui-MoE-5B-A1.7B-abliterated-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
GGUF	i1-IQ1_S	1.4	for the desperate
GGUF	i1-IQ1_M	1.5	mostly desperate
GGUF	i1-IQ2_XXS	1.6
GGUF	i1-IQ2_XS	1.8
GGUF	i1-IQ2_S	1.8
GGUF	i1-IQ2_M	2.0
GGUF	i1-Q2K_S	2.0	very low quality
GGUF	i1-Q2K	2.1	IQ3XXS probably better
GGUF	i1-IQ3_XXS	2.2	lower quality
GGUF	i1-IQ3_XS	2.4
GGUF	i1-IQ3S	2.5	beats Q3K*
GGUF	i1-Q3KS	2.5	IQ3XS probably better
GGUF	i1-IQ3_M	2.5
GGUF	i1-Q3KM	2.7	IQ3S probably better
GGUF	i1-Q3KL	2.9	IQ3M probably better
GGUF	i1-IQ4_XS	3.0
GGUF	i1-IQ4NL	3.1	prefer IQ4XS
GGUF	i1-Q4_0	3.1	fast, low quality
GGUF	i1-Q4K_S	3.1	optimal size/speed/quality
GGUF	i1-Q4K_M	3.3	fast, recommended
GGUF	i1-Q4_1	3.4
GGUF	i1-Q5K_S	3.7
GGUF	i1-Q5K_M	3.8
GGUF	i1-Q6K	4.4	practically like static Q6K

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

!image.png

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. Additional thanks to @nicoboss for giving me access to his private supercomputer, enabling me to provide many more imatrix quants, at much higher quality, than I would otherwise be able to.