mradermacher/Noromaid-v0.4-Mixtral-Instruct-8x7b-Zloss-GGUF

About

static quants of https://huggingface.co/NeverSleep/Noromaid-v0.4-Mixtral-Instruct-8x7b-Zloss

weighted/imatrix quants are available at https://huggingface.co/mradermacher/Noromaid-v0.4-Mixtral-Instruct-8x7b-Zloss-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	17.8
GGUF	IQ3_XS	19.8
GGUF	IQ3_S	20.9	beats Q3_K*
GGUF	Q3_K_S	20.9
GGUF	IQ3_M	21.9
GGUF	Q3_K_M	23.1	lower quality
GGUF	Q3_K_L	24.7
GGUF	IQ4_XS	25.9
GGUF	Q4_K_S	27.3	fast, recommended
GGUF	Q4_K_M	29.0	fast, recommended
GGUF	Q5_K_S	32.7
GGUF	Q5_K_M	33.7
GGUF	Q6_K	38.9	very good quality
PART 1 PART 2	Q8_0	50.1	fast, best quality
PART 1 PART 2 PART 3 PART 4	SOURCE	186.9	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.