Transformers
GGUF
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imatrix
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metadata
base_model: lightblue/qarasu-14B-chat-plus-unleashed
datasets:
  - OpenAssistant/oasst1
  - zetavg/ShareGPT-Processed
  - augmxnt/ultra-orca-boros-en-ja-v1
language:
  - ja
  - en
library_name: transformers
license: other
license_link: >-
  https://github.com/QwenLM/Qwen/blob/main/Tongyi%20Qianwen%20LICENSE%20AGREEMENT
license_name: tongyi-qianwen-license-agreement
quantized_by: mradermacher

About

weighted/imatrix quants of https://huggingface.co/lightblue/qarasu-14B-chat-plus-unleashed

static quants are available at https://huggingface.co/mradermacher/qarasu-14B-chat-plus-unleashed-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 4.5 for the desperate
GGUF i1-IQ1_M 4.7 mostly desperate
GGUF i1-IQ2_XXS 5.0
GGUF i1-IQ2_XS 5.3
GGUF i1-IQ2_S 5.5
GGUF i1-IQ2_M 5.8
GGUF i1-Q2_K_S 5.8 very low quality
GGUF i1-Q2_K 5.9 IQ3_XXS probably better
GGUF i1-IQ3_XXS 6.4 lower quality
GGUF i1-Q3_K_S 6.9 IQ3_XS probably better
GGUF i1-IQ3_M 7.5
GGUF i1-Q3_K_M 7.8 IQ3_S probably better
GGUF i1-IQ4_XS 7.9
GGUF i1-Q3_K_L 8.1 IQ3_M probably better
GGUF i1-Q4_0_4_4 8.3 fast on arm, low quality
GGUF i1-Q4_K_S 8.7 optimal size/speed/quality
GGUF i1-Q4_K_M 9.5 fast, recommended
GGUF i1-Q5_K_S 10.1
GGUF i1-Q6_K 12.4 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.