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metadata
base_model: ibivibiv/giant-hydra-moe-240b
language:
  - en
library_name: transformers
license: llama2
quantized_by: mradermacher
tags:
  - moe
  - moerge

About

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

weighted/imatrix quants are available at https://huggingface.co/mradermacher/giant-hydra-moe-240b-i1-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 Q2_K 87.6
PART 1 PART 2 Q3_K_XS 96.5
PART 1 PART 2 PART 3 Q3_K_S 103.5
PART 1 PART 2 PART 3 Q3_K_M 114.8 lower quality
PART 1 PART 2 PART 3 Q3_K_L 124.3
PART 1 PART 2 PART 3 Q4_K_S 136.2 fast, recommended
PART 1 PART 2 PART 3 Q4_K_M 144.8 fast, recommended
PART 1 PART 2 PART 3 PART 4 Q5_K_S 164.7
PART 1 PART 2 PART 3 PART 4 Q5_K_M 169.7
P1 P2 P3 P4 P5 Q6_K 196.3 very good quality
P1 P2 P3 P4 P5 P6 Q8_0 253.9 fast, best quality

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.