Plap-8x13B-i1-GGUF / README.md
mradermacher's picture
auto-patch README.md
c87449d verified
metadata
base_model: MergeFuel/Plap-8x13B
language:
  - en
library_name: transformers
license: cc-by-nc-4.0
no_imatrix: crash
quantized_by: mradermacher
tags:
  - not-for-all-audiences
  - nsfw

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.