mradermacher/Megac4ai-command-r-plus-GGUF

About

static quants of https://huggingface.co/nitky/Megac4ai-command-r-plus

weighted/imatrix quants are available at https://huggingface.co/mradermacher/Megac4ai-command-r-plus-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
PART 1 PART 2	Q2_K	60.4
PART 1 PART 2	IQ3_XS	66.8
PART 1 PART 2	Q3_K_S	70.3
PART 1 PART 2	IQ3_S	70.5	beats Q3_K*
PART 1 PART 2	IQ3_M	73.1
PART 1 PART 2	Q3_K_M	78.3	lower quality
PART 1 PART 2	Q3_K_L	85.2
PART 1 PART 2	IQ4_XS	87.2
PART 1 PART 2	Q4_K_S	91.8	fast, recommended
PART 1 PART 2	Q4_K_M	96.7	fast, recommended
PART 1 PART 2 PART 3	Q5_K_S	110.8
PART 1 PART 2 PART 3	Q5_K_M	113.7
PART 1 PART 2 PART 3	Q6_K	131.7	very good quality
PART 1 PART 2 PART 3 PART 4	Q8_0	170.6	fast, best quality
P1 P2 P3 P4 P5 P6 P7	SOURCE	321.0	source gguf, only provided when it was hard to come by

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.