About

static quants of https://huggingface.co/rinna/nekomata-14b

weighted/imatrix quants are available at https://huggingface.co/mradermacher/nekomata-14b-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 5.9
GGUF IQ3_XS 6.7
GGUF IQ3_S 6.9 beats Q3_K*
GGUF Q3_K_S 6.9
GGUF IQ3_M 7.5
GGUF Q3_K_M 7.8 lower quality
GGUF IQ4_XS 8.0
GGUF Q3_K_L 8.1
GGUF Q4_K_S 8.7 fast, recommended
GGUF Q4_K_M 9.5 fast, recommended
GGUF Q5_K_S 10.1
GGUF Q5_K_M 11.0
GGUF Q6_K 12.4 very good quality
GGUF Q8_0 15.2 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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qwen

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Model tree for mradermacher/nekomata-14b-GGUF

Base model

Qwen/Qwen-14B
Finetuned
rinna/nekomata-14b
Quantized
(3)
this model

Datasets used to train mradermacher/nekomata-14b-GGUF