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metadata
base_model: DisOOM/Qwen1.5-55B-Chat-Cut
language:
  - en
  - chi
library_name: transformers
license: other
license_link: https://huggingface.co/Qwen/Qwen1.5-72B-Chat/blob/main/LICENSE
license_name: tongyi-qianwen
quantized_by: mradermacher
tags:
  - merge
  - mergekit
  - qwen2
  - chat
  - conversational

About

weighted/imatrix quants of https://huggingface.co/DisOOM/Qwen1.5-55B-Chat-Cut

static quants are available at https://huggingface.co/mradermacher/Qwen1.5-55B-Chat-Cut-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_M 13.6 mostly desperate
GGUF i1-IQ2_M 19.3
GGUF i1-Q2_K 20.8 IQ3_XXS probably better
GGUF i1-IQ3_XXS 21.2 lower quality
GGUF i1-Q3_K_S 24.2 IQ3_XS probably better
GGUF i1-IQ3_M 25.4
GGUF i1-Q3_K_M 26.9 IQ3_S probably better
GGUF i1-IQ4_XS 29.6
GGUF i1-Q4_K_S 31.5 optimal size/speed/quality
GGUF i1-Q4_K_M 33.4 fast, recommended
GGUF i1-Q6_K 45.1 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.