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metadata
exported_from: ParasiticRogue/Nyakura-CausalLM-RP-34B
language:
  - en
library_name: transformers
license: other
license_link: https://huggingface.co/01-ai/Yi-34B-200K/blob/main/LICENSE
license_name: yi-34b
quantized_by: mradermacher
tags:
  - mergekit
  - merge

About

weighted/imatrix quants of https://huggingface.co/ParasiticRogue/Nyakura-CausalLM-RP-34B

static quants are available at https://huggingface.co/mradermacher/Nyakura-CausalLM-RP-34B-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 11.9
GGUF i1-Q2_K 12.9 IQ3_XXS probably better
GGUF i1-IQ3_XXS 13.4 lower quality
GGUF i1-Q3_K_S 15.1 IQ3_XS probably better
GGUF i1-Q3_K_M 16.8 IQ3_S probably better
GGUF i1-Q3_K_L 18.2 IQ3_M probably better
GGUF i1-IQ4_XS 18.6
GGUF i1-Q4_K_S 19.7 optimal size/speed/quality
GGUF i1-Q4_K_M 20.8 fast, recommended
GGUF i1-Q5_K_S 23.8
GGUF i1-Q6_K 28.3 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.