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mradermacher/WizardLM-2-8x22B-Beige-i1-GGUF

sourceHugging Faceupdated 2y agoView on Hugging Face
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About

<!-- ### quantizeversion: 2 --> <!-- ### outputtensorquantised: 1 --> <!-- ### converttype: hf --> <!-- ### vocab_type: --> <!-- ### tags: nicoboss --> weighted/imatrix quants of https://huggingface.co/gghfez/WizardLM-2-8x22B-Beige

<!-- provided-files --> static quants are available at https://huggingface.co/mradermacher/WizardLM-2-8x22B-Beige-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)

LinkTypeSize/GBNotes
GGUFi1-IQ1_S29.7for the desperate
GGUFi1-IQ1_M32.8mostly desperate
GGUFi1-IQ2_XXS38.0
GGUFi1-IQ2_XS42.1
GGUFi1-IQ2_S42.7
GGUFi1-IQ2_M46.8
PART 1 PART 2i1-Q2_K52.2IQ3_XXS probably better
PART 1 PART 2i1-IQ3_XXS55.0lower quality
PART 1 PART 2i1-IQ3_XS58.3
PART 1 PART 2i1-IQ3_S61.6beats Q3_K*
PART 1 PART 2i1-Q3KS61.6IQ3_XS probably better
PART 1 PART 2i1-IQ3_M64.6
PART 1 PART 2i1-Q3KM67.9IQ3_S probably better
PART 1 PART 2i1-Q3KL72.7IQ3_M probably better
PART 1 PART 2i1-IQ4_XS75.6
PART 1 PART 2i1-Q4_080.0fast, low quality
PART 1 PART 2i1-Q4KS80.6optimal size/speed/quality
PART 1 PART 2i1-Q4KM85.7fast, recommended
PART 1 PART 2i1-Q5KS97.1
PART 1 PART 2 PART 3i1-Q5KM100.1
PART 1 PART 2 PART 3i1-Q6_K115.6practically like static Q6_K

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. 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.

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