mradermacher/codegemma-7b-GGUF

About

static quants of https://huggingface.co/google/codegemma-7b

weighted/imatrix quants are available at https://huggingface.co/mradermacher/codegemma-7b-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	Q4_0_4_4	5.1	fast on arm, low quality
PART 1 PART 2	Q2_K	7.1
PART 1 PART 2	Q3_K_S	8.1
PART 1 PART 2	Q3_K_M	8.8	lower quality
PART 1 PART 2	Q3_K_L	9.5
PART 1 PART 2	IQ4_XS	9.7
PART 1 PART 2	Q4_K_S	10.2	fast, recommended
PART 1 PART 2	Q4_K_M	10.8	fast, recommended
PART 1 PART 2	Q5_K_S	12.1
PART 1 PART 2	Q5_K_M	12.4
PART 1 PART 2	Q6_K	14.1	very good quality
PART 1 PART 2	Q8_0	18.3	fast, best quality
PART 1 PART 2	f16	34.3	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.