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mradermacher/aya-23-35B-i1-GGUF

sourceHugging Facecc-by-nc-4.0updated 1y agoView on Hugging Face

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Model Card

About

weighted/imatrix quants of https://huggingface.co/CohereLabs/aya-23-35B

static quants are available at https://huggingface.co/mradermacher/aya-23-35B-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	i1-IQ1_S	8.6	for the desperate
GGUF	i1-IQ1_M	9.2	mostly desperate
GGUF	i1-IQ2_XXS	10.3
GGUF	i1-IQ2_XS	11.2
GGUF	i1-IQ2_S	11.9
GGUF	i1-IQ2_M	12.8
GGUF	i1-Q2_K	13.9	IQ3_XXS probably better
GGUF	i1-IQ3_XXS	13.9	lower quality
GGUF	i1-IQ3_XS	15.2
GGUF	i1-IQ3_S	16.0	beats Q3_K*
GGUF	i1-Q3KS	16.0	IQ3_XS probably better
GGUF	i1-IQ3_M	16.8
GGUF	i1-Q3KM	17.7	IQ3_S probably better
GGUF	i1-Q3KL	19.2	IQ3_M probably better
GGUF	i1-IQ4_XS	19.3
GGUF	i1-Q4_0	20.4	fast, low quality
GGUF	i1-Q4KS	20.5	optimal size/speed/quality
GGUF	i1-Q4KM	21.6	fast, recommended
GGUF	i1-Q5KS	24.4
GGUF	i1-Q5KM	25.1
GGUF	i1-Q6_K	28.8	practically like static Q6_K

Here is a handy graph by ikawrakow comparing some lower-quality quant types (lower is better):

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.