About

weighted/imatrix quants of https://huggingface.co/MergeFuel/Plap-8x13B

static quants are available at https://huggingface.co/mradermacher/Plap-8x13B-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_M 24.8
GGUF i1-Q2_K 28.4 IQ3_XXS probably better
GGUF i1-Q3_K_S 33.1 IQ3_XS probably better
GGUF i1-Q3_K_M 36.2 IQ3_S probably better
GGUF i1-Q3_K_L 38.7 IQ3_M probably better
GGUF i1-Q4_K_S 42.6 optimal size/speed/quality
GGUF i1-Q4_K_M 45.2 fast, recommended
PART 1 PART 2 i1-Q5_K_S 50.9
PART 1 PART 2 i1-Q5_K_M 52.4
PART 1 PART 2 i1-Q6_K 60.3 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
10
GGUF
Model size
72.5B params
Architecture
llama

2-bit

3-bit

4-bit

Inference Providers NEW
This model is not currently available via any of the supported third-party Inference Providers, and HF Inference API was unable to determine this model’s pipeline type.

Model tree for mradermacher/Plap-8x13B-i1-GGUF

Quantized
(2)
this model