Tema_Q-R7.0-GGUF / README.md
mradermacher's picture
auto-patch README.md
96f7a50 verified
metadata
base_model: temaq-org/Tema_Q-R7.0
language:
  - ja
  - en
library_name: transformers
license: gemma
mradermacher:
  readme_rev: 1
quantized_by: mradermacher
tags:
  - gemma3
  - gemma
  - transformer
  - instruction-tuned
  - multilingual
  - uncensored
  - non-censored
  - unfiltered

About

static quants of https://huggingface.co/temaq-org/Tema_Q-R7.0

For a convenient overview and download list, visit our model page for this model.

weighted/imatrix quants are available at https://huggingface.co/mradermacher/Tema_Q-R7.0-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 mmproj-Q8_0 0.7 multi-modal supplement
GGUF mmproj-f16 1.0 multi-modal supplement
GGUF Q2_K 4.9
GGUF Q3_K_S 5.6
GGUF Q3_K_M 6.1 lower quality
GGUF Q3_K_L 6.6
GGUF IQ4_XS 6.7
GGUF Q4_K_S 7.0 fast, recommended
GGUF Q4_K_M 7.4 fast, recommended
GGUF Q5_K_S 8.3
GGUF Q5_K_M 8.5
GGUF Q6_K 9.8 very good quality
GGUF Q8_0 12.6 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.