mradermacher's picture
auto-patch README.md
153f57a verified
metadata
base_model: MaziyarPanahi/Llama-3-13B-Instruct-v0.1
language:
  - en
library_name: transformers
license: other
license_link: LICENSE
license_name: llama3
model_creator: MaziyarPanahi
model_name: Llama-3-13B-Instruct-v0.1
quantized_by: mradermacher
tags:
  - mergekit
  - merge
  - facebook
  - meta
  - pytorch
  - llama
  - llama-3

About

weighted/imatrix quants of https://huggingface.co/MaziyarPanahi/Llama-3-13B-Instruct-v0.1

static quants are available at https://huggingface.co/mradermacher/Llama-3-13B-Instruct-v0.1-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 3.2 for the desperate
GGUF i1-IQ1_M 3.5 mostly desperate
GGUF i1-IQ2_XXS 3.9
GGUF i1-IQ2_XS 4.3
GGUF i1-IQ2_S 4.5
GGUF i1-IQ2_M 4.8
GGUF i1-Q2_K_S 4.9 very low quality
GGUF i1-Q2_K 5.2 IQ3_XXS probably better
GGUF i1-IQ3_XXS 5.4 lower quality
GGUF i1-IQ3_XS 5.8
GGUF i1-Q3_K_S 6.0 IQ3_XS probably better
GGUF i1-IQ3_S 6.0 beats Q3_K*
GGUF i1-IQ3_M 6.2
GGUF i1-Q3_K_M 6.6 IQ3_S probably better
GGUF i1-Q3_K_L 7.2 IQ3_M probably better
GGUF i1-IQ4_XS 7.3
GGUF i1-Q4_0_4_4 7.7 fast on arm, low quality
GGUF i1-Q4_0_4_8 7.7 fast on arm+i8mm, low quality
GGUF i1-Q4_0_8_8 7.7 fast on arm+sve, low quality
GGUF i1-Q4_0 7.7 fast, low quality
GGUF i1-Q4_K_S 7.8 optimal size/speed/quality
GGUF i1-Q4_K_M 8.2 fast, recommended
GGUF i1-Q5_K_S 9.3
GGUF i1-Q5_K_M 9.5
GGUF i1-Q6_K 11.0 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. 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.