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mradermacher/bert-tiny-book-text-classifier-i1-GGUF

sourceHugging Facemitupdated 1y 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/shhossain/bert-tiny-book-text-classifier

<!-- provided-files --> static quants are available at https://huggingface.co/mradermacher/bert-tiny-book-text-classifier-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_S0.1for the desperate
GGUFi1-IQ1_M0.1mostly desperate
GGUFi1-IQ2_XXS0.1
GGUFi1-IQ2_S0.1
GGUFi1-IQ2_XS0.1
GGUFi1-IQ2_M0.1
GGUFi1-Q2KS0.1very low quality
GGUFi1-IQ3_XXS0.1lower quality
GGUFi1-IQ3_S0.1beats Q3_K*
GGUFi1-IQ3_XS0.1
GGUFi1-Q2_K0.1IQ3_XXS probably better
GGUFi1-Q3KS0.1IQ3_XS probably better
GGUFi1-IQ3_M0.1
GGUFi1-IQ4_XS0.1
GGUFi1-IQ4_NL0.1prefer IQ4_XS
GGUFi1-Q4_00.1fast, low quality
GGUFi1-Q3KM0.1IQ3_S probably better
GGUFi1-Q4_10.1
GGUFi1-Q3KL0.1IQ3_M probably better
GGUFi1-Q4KS0.1optimal size/speed/quality
GGUFi1-Q4KM0.1fast, recommended
GGUFi1-Q5KS0.1
GGUFi1-Q5KM0.1
GGUFi1-Q6_K0.1practically 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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