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mradermacher/KernelBench-RLVR-120b-GGUF

sourceHugging Faceapache-2.0updated 1mo agoView on Hugging Face
0likes473downloads
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About

<!-- ### quantizeversion: 2 --> <!-- ### outputtensorquantised: 1 --> <!-- ### converttype: hf --> <!-- ### vocabtype: --> <!-- ### tags: --> <!-- ### quants: x-f16 Q4KS Q2K Q80 Q6K Q3KM Q3KS Q3KL Q4KM Q5KS Q5KM IQ4XS --> <!-- ### quantsskip: --> <!-- ### skip_mmproj: --> static quants of https://huggingface.co/Jarrodbarnes/KernelBench-RLVR-120b

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*For a convenient overview and download list, visit our [model page for this model](https://hf.tst.eu/model#KernelBench-RLVR-120b-GGUF).*

weighted/imatrix quants are available at https://huggingface.co/mradermacher/KernelBench-RLVR-120b-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)

LinkTypeSize/GBNotes
GGUFQ3KS66.2
GGUFQ2_K66.3
GGUFIQ4_XS67.1
GGUFQ3KM71.2lower quality
GGUFQ3KL73.5
GGUFQ4KS81.0fast, recommended
GGUFQ4KM88.0fast, recommended
GGUFQ5KS88.1
GGUFQ5KM94.0
PART 1 PART 2 PART 3Q6_K124.3very good quality
PART 1 PART 2 PART 3Q8_0124.4fast, 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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