base_model, datasets, language, library_name, license, quantized_by, tags

base_model	datasets	language	library_name	license	quantized_by	tags
EpistemeAI/EpistemeAI-codegemma-2-9b	TokenBender/code_instructions_122k_alpaca_style	en	transformers	gemma	mradermacher	text-generation-inference transformers unsloth gemma2 trl

About

static quants of https://huggingface.co/EpistemeAI/EpistemeAI-codegemma-2-9b

weighted/imatrix quants are available at https://huggingface.co/mradermacher/EpistemeAI-codegemma-2-9b-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	3.9
GGUF	IQ3_XS	4.2
GGUF	IQ3_S	4.4	beats Q3_K*
GGUF	Q3_K_S	4.4
GGUF	IQ3_M	4.6
GGUF	Q3_K_M	4.9	lower quality
GGUF	Q3_K_L	5.2
GGUF	IQ4_XS	5.3
GGUF	Q4_K_S	5.6	fast, recommended
GGUF	Q4_K_M	5.9	fast, recommended
GGUF	Q5_K_S	6.6
GGUF	Q5_K_M	6.7
GGUF	Q6_K	7.7	very good quality
GGUF	Q8_0	9.9	fast, best quality
GGUF	f16	18.6	16 bpw, overkill

Here is a handy graph by ikawrakow comparing some lower-quality quant types (lower is better):

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.