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About

static quants of https://huggingface.co/pphuc25/Vistral-7B-ties

weighted/imatrix quants seem not to be available (by me) at this time. If they do not show up a week or so after the static ones, I have probably not planned for them. Feel free to request them by opening a Community Discussion.

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 2.3
GGUF IQ3_XS 2.6
GGUF Q3_K_S 2.7
GGUF IQ3_S 2.7 beats Q3_K*
GGUF IQ3_M 2.8
GGUF Q3_K_M 2.9 lower quality
GGUF Q3_K_L 3.2
GGUF IQ4_XS 3.3
GGUF Q4_0 3.4 fast, low quality
GGUF Q4_K_S 3.4 fast, recommended
GGUF IQ4_NL 3.4 prefer IQ4_XS
GGUF Q4_K_M 3.6 fast, recommended
GGUF Q5_K_S 4.1
GGUF Q5_K_M 4.2
GGUF Q6_K 4.8 very good quality
GGUF Q8_0 6.1 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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Architecture
llama

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Inference API
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