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metadata
base_model: google/codegemma-7b
extra_gated_button_content: Acknowledge license
extra_gated_heading: Access CodeGemma on Hugging Face
extra_gated_prompt: >-
  To access CodeGemma on Hugging Face, you’re required to review and agree to
  Google’s usage license. To do this, please ensure you’re logged-in to Hugging
  Face and click below. Requests are processed immediately.
language:
  - en
library_name: transformers
license: gemma
license_link: https://ai.google.dev/gemma/terms
quantized_by: mradermacher

About

weighted/imatrix quants of https://huggingface.co/google/codegemma-7b

static quants are available at https://huggingface.co/mradermacher/codegemma-7b-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 i1-IQ1_S 2.3 for the desperate
GGUF i1-IQ1_M 2.4 mostly desperate
GGUF i1-IQ2_XXS 2.7
GGUF i1-IQ2_XS 2.9
GGUF i1-IQ2_S 3.0
GGUF i1-IQ2_M 3.2
GGUF i1-Q2_K 3.6 IQ3_XXS probably better
GGUF i1-IQ3_XXS 3.6 lower quality
GGUF i1-IQ3_XS 3.9
GGUF i1-IQ3_S 4.1 beats Q3_K*
GGUF i1-Q3_K_S 4.1 IQ3_XS probably better
GGUF i1-IQ3_M 4.2
GGUF i1-Q3_K_M 4.5 IQ3_S probably better
GGUF i1-Q3_K_L 4.8 IQ3_M probably better
GGUF i1-IQ4_XS 4.9
GGUF i1-Q4_0_4_4 5.1 fast on arm, low quality
GGUF i1-Q4_0_4_8 5.1 fast on arm+i8mm, low quality
GGUF i1-Q4_0_8_8 5.1 fast on arm+sve, low quality
GGUF i1-Q4_0 5.1 fast, low quality
GGUF i1-Q4_K_S 5.1 optimal size/speed/quality
GGUF i1-Q4_K_M 5.4 fast, recommended
GGUF i1-Q5_K_S 6.1
GGUF i1-Q5_K_M 6.2
GGUF i1-Q6_K 7.1 practically like static Q6_K

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.