About

static quants of https://huggingface.co/Edentns/DataVortexS-10.7B-v1.0

weighted/imatrix quants are available at https://huggingface.co/mradermacher/DataVortexS-10.7B-v1.0-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
GGUF Q2_K 4.1
GGUF Q3_K_S 4.8
GGUF Q3_K_M 5.3 lower quality
GGUF Q3_K_L 5.8
GGUF IQ4_XS 5.9
GGUF Q4_0_4_4 6.2 fast on arm, low quality
GGUF Q4_K_S 6.2 fast, recommended
GGUF Q4_K_M 6.6 fast, recommended
GGUF Q5_K_S 7.5
GGUF Q5_K_M 7.7
GGUF Q6_K 8.9 very good quality
GGUF Q8_0 11.5 fast, best quality
GGUF f16 21.6 16 bpw, overkill

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.

Downloads last month
345
GGUF
Model size
10.7B params
Architecture
llama

2-bit

3-bit

4-bit

5-bit

6-bit

8-bit

16-bit

Inference Examples
This model does not have enough activity to be deployed to Inference API (serverless) yet. Increase its social visibility and check back later, or deploy to Inference Endpoints (dedicated) instead.

Model tree for mradermacher/DataVortexS-10.7B-v1.0-GGUF

Quantized
(4)
this model