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metadata
base_model: MaziyarPanahi/Calme-4x7B-MoE-v0.2
language:
  - en
library_name: transformers
license: apache-2.0
model_creator: MaziyarPanahi
model_name: Calme-4x7B-MoE-v0.2
quantized_by: mradermacher
tags:
  - generated_from_trainer
  - mistral
  - 7b
  - calme
  - moe
  - mixtral

About

static quants of https://huggingface.co/MaziyarPanahi/Calme-4x7B-MoE-v0.2

weighted/imatrix quants are available at https://huggingface.co/mradermacher/Calme-4x7B-MoE-v0.2-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 8.9
GGUF Q3_K_S 10.5
GGUF Q3_K_M 11.7 lower quality
GGUF Q3_K_L 12.6
GGUF IQ4_XS 13.1
GGUF Q4_K_S 13.8 fast, recommended
GGUF Q4_K_M 14.7 fast, recommended
GGUF Q5_K_S 16.7
GGUF Q5_K_M 17.2
GGUF Q6_K 19.9 very good quality
GGUF Q8_0 25.8 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. 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.