base_model, language, library_name, license, mradermacher, quantized_by, tags

base_model	language	library_name	license	mradermacher	quantized_by	tags
Nabbers1999/gemma-3-27b-it-abliterated-refined-novis	en	transformers	gemma	readme_rev 1	mradermacher	gemma gemma-3 text-generation conversational abliterated

About

static quants of https://huggingface.co/Nabbers1999/gemma-3-27b-it-abliterated-refined-novis

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

weighted/imatrix quants are available at https://huggingface.co/mradermacher/gemma-3-27b-it-abliterated-refined-novis-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
GGUF	Q2_K	10.6
GGUF	Q3_K_S	12.3
GGUF	Q3_K_M	13.5	lower quality
GGUF	Q3_K_L	14.6
GGUF	IQ4_XS	15.0
GGUF	Q4_K_S	15.8	fast, recommended
GGUF	Q4_K_M	16.6	fast, recommended
GGUF	Q5_K_S	18.9
GGUF	Q5_K_M	19.4
GGUF	Q6_K	22.3	very good quality
GGUF	Q8_0	28.8	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.