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metadata
base_model: HiroseKoichi/Llama-Salad-4x8B
language:
  - en
library_name: transformers
license: llama3
quantized_by: mradermacher
tags:
  - nsfw
  - not-for-all-audiences
  - llama-3
  - text-generation-inference

About

weighted/imatrix quants of https://huggingface.co/HiroseKoichi/Llama-Salad-4x8B

static quants are available at https://huggingface.co/mradermacher/Llama-Salad-4x8B-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-IQ2_XXS 6.9
GGUF i1-IQ2_M 8.5
GGUF i1-Q2_K 9.4 IQ3_XXS probably better
GGUF i1-IQ3_XXS 9.9 lower quality
GGUF i1-IQ3_XS 10.5
GGUF i1-Q3_K_S 11.0 IQ3_XS probably better
GGUF i1-IQ3_S 11.1 beats Q3_K*
GGUF i1-IQ3_M 11.2
GGUF i1-Q3_K_M 12.2 IQ3_S probably better
GGUF i1-Q3_K_L 13.1 IQ3_M probably better
GGUF i1-IQ4_XS 13.5
GGUF i1-Q4_0 14.3 fast, low quality
GGUF i1-Q4_K_S 14.4 optimal size/speed/quality
GGUF i1-Q4_K_M 15.3 fast, recommended
GGUF i1-Q5_K_S 17.3
GGUF i1-Q5_K_M 17.8
GGUF i1-Q6_K 20.6 practically like static Q6_K

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.