QwenGuard-v1.2-7B-GGUF/README.md

base_model, datasets, extra_gated_fields, extra_gated_prompt, language, library_name, mradermacher, quantized_by, tags

base_model	datasets	extra_gated_fields	extra_gated_prompt	language	library_name	mradermacher	quantized_by	tags
AIML-TUDA/QwenGuard-v1.2-7B	AIML-TUDA/LlavaGuard	Affiliation Country Email I have explicitly checked that downloading LlavaGuard is legal in my jurisdiction, in the country/region where I am located right now, and for the use case that I have described above, I have also read and accepted the relevant Terms of Use Name text text text checkbox text	By filling out the form below I understand that LlavaGuard is a derivative model based on webscraped images and the SMID dataset that use individual licenses and their respective terms and conditions apply. I understand that all content uses are subject to the terms of use. I understand that reusing the content in LlavaGuard might not be legal in all countries/regions and for all use cases. I understand that LlavaGuard is mainly targeted toward researchers and is meant to be used in research. LlavaGuard authors reserve the right to revoke my access to this data. They reserve the right to modify this data at any time in accordance with take-down requests.	en	transformers	readme_rev 1	mradermacher	llama-factory freeze generated_from_trainer

About

static quants of https://huggingface.co/AIML-TUDA/QwenGuard-v1.2-7B

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

weighted/imatrix quants seem not to be available (by me) at this time. If they do not show up a week or so after the static ones, I have probably not planned for them. Feel free to request them by opening a Community Discussion.

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	mmproj-Q8_0	1.0	multi-modal supplement
GGUF	mmproj-f16	1.5	multi-modal supplement
GGUF	Q2_K	3.1
GGUF	Q3_K_S	3.6
GGUF	Q3_K_M	3.9	lower quality
GGUF	Q3_K_L	4.2
GGUF	IQ4_XS	4.4
GGUF	Q4_K_S	4.6	fast, recommended
GGUF	Q4_K_M	4.8	fast, recommended
GGUF	Q5_K_S	5.4
GGUF	Q5_K_M	5.5
GGUF	Q6_K	6.4	very good quality
GGUF	Q8_0	8.2	fast, best quality
GGUF	f16	15.3	16 bpw, overkill

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.