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About

static quants of https://huggingface.co./Salesforce/xLAM-8x7b-r

weighted/imatrix quants are available at https://huggingface.co./mradermacher/xLAM-8x7b-r-i1-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 Q2_K 17.4
GGUF Q3_K_S 20.5
GGUF Q3_K_M 22.6 lower quality
GGUF Q3_K_L 24.3
GGUF IQ4_XS 25.5
GGUF Q4_K_S 26.8 fast, recommended
GGUF Q4_K_M 28.5 fast, recommended
GGUF Q5_K_S 32.3
GGUF Q5_K_M 33.3
GGUF Q6_K 38.5 very good quality
GGUF Q8_0 49.7 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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Dataset used to train mradermacher/xLAM-8x7b-r-GGUF