Edit model card

About

weighted/imatrix quants of https://huggingface.co/Undi95/Mixtral-8x7B-MoE-RP-Story

static quants are available at https://huggingface.co/mradermacher/Mixtral-8x7B-MoE-RP-Story-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-IQ1_S 10.1 for the desperate
GGUF i1-IQ2_XXS 12.8
GGUF i1-IQ2_XS 14.2
GGUF i1-IQ2_S 14.4
GGUF i1-IQ2_M 15.8
GGUF i1-Q2_K 17.6 IQ3_XXS probably better
GGUF i1-IQ3_XXS 18.5 lower quality
GGUF i1-IQ3_XS 19.5
GGUF i1-IQ3_S 20.7 beats Q3_K*
GGUF i1-Q3_K_S 20.7 IQ3_XS probably better
GGUF i1-IQ3_M 21.7
GGUF i1-Q3_K_M 22.8 IQ3_S probably better
GGUF i1-Q3_K_L 24.4 IQ3_M probably better
GGUF i1-IQ4_XS 25.3
GGUF i1-Q4_K_S 27.0 optimal size/speed/quality
GGUF i1-Q4_K_M 28.7 fast, recommended
GGUF i1-Q5_K_S 32.5
GGUF i1-Q5_K_M 33.5
GGUF i1-Q6_K 38.6 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.

Downloads last month
503
GGUF
Model size
46.7B params
Architecture
llama

1-bit

2-bit

3-bit

4-bit

5-bit

6-bit

Inference API
Unable to determine this model’s pipeline type. Check the docs .

Model tree for mradermacher/Mixtral-8x7B-MoE-RP-Story-i1-GGUF

Quantized
(5)
this model