About

static quants of https://huggingface.co./MaziyarPanahi/calme-2.4-rys-78b

weighted/imatrix quants are available at https://huggingface.co./mradermacher/calme-2.4-rys-78b-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 31.9
GGUF IQ3_XS 35.2
GGUF Q3_K_S 36.9
GGUF IQ3_S 37.0 beats Q3_K*
GGUF IQ3_M 38.0
GGUF Q3_K_M 40.4 lower quality
GGUF Q3_K_L 42.4
GGUF IQ4_XS 43.1
GGUF Q4_K_S 47.0 fast, recommended
PART 1 PART 2 Q4_K_M 50.8 fast, recommended
PART 1 PART 2 Q5_K_S 55.2
PART 1 PART 2 Q5_K_M 58.4
PART 1 PART 2 Q6_K 69.1 very good quality
PART 1 PART 2 Q8_0 83.0 fast, best quality

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.

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GGUF
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qwen2

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Model tree for mradermacher/calme-2.4-rys-78b-GGUF

Base model

dnhkng/RYS-XLarge
Quantized
(5)
this model

Datasets used to train mradermacher/calme-2.4-rys-78b-GGUF