About

static quants of https://huggingface.co/theprint/ReWiz-Qwen-2.5-14B

weighted/imatrix quants are available at https://huggingface.co/mradermacher/ReWiz-Qwen-2.5-14B-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 11.6
PART 1 PART 2 Q3_K_S 13.4
PART 1 PART 2 Q3_K_M 14.8 lower quality
PART 1 PART 2 Q3_K_L 15.9
PART 1 PART 2 IQ4_XS 16.5
PART 1 PART 2 Q4_0_4_4 17.1 fast on arm, low quality
PART 1 PART 2 Q4_K_S 17.2 fast, recommended
PART 1 PART 2 Q4_K_M 18.1 fast, recommended
PART 1 PART 2 Q5_K_S 20.6
PART 1 PART 2 Q5_K_M 21.1
PART 1 PART 2 Q6_K 24.3 very good quality
PART 1 PART 2 Q8_0 31.5 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.

Downloads last month
411
GGUF
Model size
14.8B params
Architecture
qwen2

2-bit

3-bit

4-bit

5-bit

6-bit

8-bit

Inference API
Unable to determine this model’s pipeline type. Check the docs .

Model tree for mradermacher/ReWiz-Qwen-2.5-14B-GGUF

Quantized
(4)
this model