mradermacher/GemmaX2-28-2B-v0.1-GGUF

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base_model: ModelSpace/GemmaX2-28-2B-v0.1 language:

• ar
• bn
• cs
• de
• en
• es
• fa
• fr
• he
• hi
• id
• it
• ja
• km
• ko
• lo
• ms
• my
• nl
• pl
• pt
• ru
• th
• tl
• tr
• ur
• vi
• zh

library_name: transformers license: gemma license_link: LICENSE license_name: license quantized_by: mradermacher

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About

static quants of https://huggingface.co/ModelSpace/GemmaX2-28-2B-v0.1

weighted/imatrix quants are available at https://huggingface.co/mradermacher/GemmaX2-28-2B-v0.1-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	1.3
GGUF	Q3K_S	1.5
GGUF	Q3K_M	1.6	lower quality
GGUF	Q3K_L	1.7
GGUF	IQ4_XS	1.7
GGUF	Q404_4	1.7	fast on arm, low quality
GGUF	Q4K_S	1.7	fast, recommended
GGUF	Q4K_M	1.8	fast, recommended
GGUF	Q5K_S	2.0
GGUF	Q5K_M	2.0
GGUF	Q6_K	2.3	very good quality
GGUF	Q8_0	2.9	fast, best quality
GGUF	f16	5.3	16 bpw, overkill

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.