aya-23-8B-i1-GGUF / README.md
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About

weighted/imatrix quants of https://huggingface.co/CohereForAI/aya-23-8B

static quants are available at https://huggingface.co/mradermacher/aya-23-8B-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 2.3 for the desperate
GGUF i1-IQ1_M 2.5 mostly desperate
GGUF i1-IQ2_XXS 2.7
GGUF i1-IQ2_XS 2.9
GGUF i1-IQ2_S 3.0
GGUF i1-IQ2_M 3.2
GGUF i1-IQ3_XXS 3.5 lower quality
GGUF i1-Q2_K 3.5 IQ3_XXS probably better
GGUF i1-IQ3_XS 3.8
GGUF i1-Q3_K_S 4.0 IQ3_XS probably better
GGUF i1-IQ3_S 4.0 beats Q3_K*
GGUF i1-IQ3_M 4.1
GGUF i1-Q3_K_M 4.3 IQ3_S probably better
GGUF i1-Q3_K_L 4.6 IQ3_M probably better
GGUF i1-IQ4_XS 4.7
GGUF i1-Q4_0 4.9 fast, low quality
GGUF i1-Q4_K_S 4.9 optimal size/speed/quality
GGUF i1-Q4_K_M 5.2 fast, recommended
GGUF i1-Q5_K_S 5.8
GGUF i1-Q5_K_M 5.9
GGUF i1-Q6_K 6.7 practically 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.