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metadata
base_model: VAGOsolutions/SauerkrautLM-Mixtral-8x7B
datasets:
  - Open-Orca/SlimOrca
  - argilla/distilabel-math-preference-dpo
language:
  - en
  - de
  - fr
  - it
  - es
library_name: transformers
license: apache-2.0
quantized_by: mradermacher
tags:
  - mistral
  - finetune
  - sft
  - dpo
  - chatml
  - augmentation
  - german
  - mixtral
  - moe

About

weighted/imatrix quants of https://huggingface.co/VAGOsolutions/SauerkrautLM-Mixtral-8x7B

static quants are available at https://huggingface.co/mradermacher/SauerkrautLM-Mixtral-8x7B-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-Q2_K 17.4 IQ3_XXS probably better
GGUF i1-IQ3_M 21.5

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. Additional thanks to @nicoboss for giving me access to his private supercomputer, enabling me to provide many more imatrix quants, at much higher quality, than I would otherwise be able to.