mradermacher/

Mixtral-8x7B-v0.1-instruct-l2-norm-post-SFT-pruned-4-experts-GGUF

static quants of https://huggingface.co/Na0s/Mixtral-8x7B-v0.1-instruct-l2-norm-post-Gates-LoRA-SFT-pruned-4-experts

weighted/imatrix quants are available at https://huggingface.co/mradermacher/Mixtral-8x7B-v0.1-instruct-l2-norm-post-SFT-pruned-4-experts-i1-GGUF

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.

(sorted by size, not necessarily quality. IQ-quants are often preferable over similar sized non-IQ quants)

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

See https://huggingface.co/mradermacher/model_requests for some answers to questions you might have and/or if you want some other model quantized.

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.