mradermacher/Fireball-Mistral-Nemo-Instruct-24B-merge-v1-GGUF

About

static quants of https://huggingface.co./EpistemeAI/Fireball-Mistral-Nemo-Instruct-24B-merge-v1

weighted/imatrix quants are available at https://huggingface.co./mradermacher/Fireball-Mistral-Nemo-Instruct-24B-merge-v1-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	4.9
GGUF	IQ3_XS	5.4
GGUF	Q3_K_S	5.6
GGUF	IQ3_S	5.7	beats Q3_K*
GGUF	IQ3_M	5.8
GGUF	Q3_K_M	6.2	lower quality
GGUF	Q3_K_L	6.7
GGUF	IQ4_XS	6.9
GGUF	Q4_K_S	7.2	fast, recommended
GGUF	Q4_K_M	7.6	fast, recommended
GGUF	Q5_K_S	8.6
GGUF	Q5_K_M	8.8
GGUF	Q6_K	10.2	very good quality
GGUF	Q8_0	13.1	fast, best quality

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.