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metadata
language:
  - en
library_name: transformers
license: llama2
quantized_by: mradermacher
tags:
  - moe
  - moerge

About

weighted quants of https://huggingface.co/ibivibiv/giant-hydra-moe-240b

static quants are available at https://huggingface.co/mradermacher/giant-hydra-moe-240b-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
PART 1 PART 2 i1-IQ1_S 49.5 for the desperate
PART 1 PART 2 i1-IQ2_XXS 63.4
PART 1 PART 2 i1-IQ2_XS 70.5
PART 1 PART 2 i1-IQ2_M 79.2
PART 1 PART 2 i1-Q2_K 87.6 IQ3_XXS probably better
PART 1 PART 2 i1-IQ3_XXS 92.7 fast, lower quality
PART 1 PART 2 i1-Q3_K_XS 96.5
PART 1 PART 2 PART 3 i1-IQ3_XS 97.4
PART 1 PART 2 PART 3 i1-Q3_K_S 103.5 IQ3_XS probably better
PART 1 PART 2 PART 3 i1-IQ3_S 103.5 fast, beats Q3_K*
PART 1 PART 2 PART 3 i1-Q3_K_M 114.8 IQ3_S probably better
PART 1 PART 2 PART 3 i1-Q3_K_L 124.3 IQ3_M probably better
PART 1 PART 2 PART 3 i1-Q4_K_S 136.2 optimal size/speed/quality
PART 1 PART 2 PART 3 i1-Q4_K_M 144.8 fast, medium quality
PART 1 PART 2 PART 3 PART 4 i1-Q5_K_S 164.7
PART 1 PART 2 PART 3 PART 4 i1-Q5_K_M 169.7
PART 1 PART 2 PART 3 PART 4 PART 5 i1-Q6_K 196.3 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

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.