NeuroCom_v2_4B-GGUF / README.md
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metadata
base_model: FourOhFour/NeuroCom_v2_4B
language:
  - en
library_name: transformers
license: apache-2.0
quantized_by: mradermacher

About

static quants of https://huggingface.co/FourOhFour/NeuroCom_v2_4B

weighted/imatrix quants are available at https://huggingface.co/mradermacher/NeuroCom_v2_4B-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 1.9
GGUF IQ3_XS 2.1
GGUF Q3_K_S 2.2
GGUF IQ3_S 2.2 beats Q3_K*
GGUF IQ3_M 2.3
GGUF Q3_K_M 2.4 lower quality
GGUF Q3_K_L 2.6
GGUF IQ4_XS 2.7
GGUF Q4_K_S 2.8 fast, recommended
GGUF Q4_K_M 2.9 fast, recommended
GGUF Q5_K_S 3.3
GGUF Q5_K_M 3.3
GGUF Q6_K 3.8 very good quality
GGUF Q8_0 4.9 fast, best quality
GGUF f16 9.1 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.