MegaQwen-120B-GGUF / README.md
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metadata
base_model: abideen/MegaQwen-120B
language:
  - en
library_name: transformers
license: apache-2.0
quantized_by: mradermacher
tags:
  - merge
  - mergekit
  - Qwen/Qwen1.5-72B

About

static quants of https://huggingface.co/abideen/MegaQwen-120B

weighted/imatrix quants seem not to be available (by me) at this time. If they do not show up a week or so after the static ones, I have probably not planned for them. Feel free to request them by opening a Community Discussion.

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 Q2_K 47.9
PART 1 PART 2 IQ3_XS 52.8
PART 1 PART 2 IQ3_S 55.6 beats Q3_K*
PART 1 PART 2 Q3_K_S 55.6
PART 1 PART 2 IQ3_M 58.6
PART 1 PART 2 Q3_K_M 62.1 lower quality
PART 1 PART 2 Q3_K_L 67.7
PART 1 PART 2 IQ4_XS 68.7
PART 1 PART 2 Q4_0 72.0 fast, low quality
PART 1 PART 2 IQ4_NL 72.4 prefer IQ4_XS
PART 1 PART 2 Q4_K_S 72.5 fast, recommended
PART 1 PART 2 Q4_K_M 76.9 fast, recommended
PART 1 PART 2 Q5_K_S 87.4
PART 1 PART 2 Q5_K_M 89.9
PART 1 PART 2 PART 3 Q6_K 103.8 very good quality
PART 1 PART 2 PART 3 Q8_0 133.7 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.