mradermacher/DeepSeek-Coder-V2-Instruct-0724-GGUF

About

static quants of https://huggingface.co/deepseek-ai/DeepSeek-Coder-V2-Instruct-0724

weighted/imatrix quants are available at https://huggingface.co/mradermacher/DeepSeek-Coder-V2-Instruct-0724-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	86.0
PART 1 PART 2	IQ3_XS	96.4
PART 1 PART 2 PART 3	IQ3_S	101.8	beats Q3_K*
PART 1 PART 2 PART 3	Q3_K_S	101.8
PART 1 PART 2 PART 3	IQ3_M	103.5
PART 1 PART 2 PART 3	Q3_K_M	112.8	lower quality
PART 1 PART 2 PART 3	Q3_K_L	122.5
PART 1 PART 2 PART 3	IQ4_XS	126.9
PART 1 PART 2 PART 3	Q4_K_S	134.0	fast, recommended
PART 1 PART 2 PART 3	Q4_K_M	142.6	fast, recommended
PART 1 PART 2 PART 3 PART 4	Q5_K_S	162.4
PART 1 PART 2 PART 3 PART 4	Q5_K_M	167.3
PART 1 PART 2 PART 3 PART 4	Q6_K	193.6	very good quality
P1 P2 P3 P4 P5 P6	Q8_0	250.7	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. 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.