StrangeMerges_51-7B-dare_ties-GGUF/README.md

base_model, language, library_name, license, mradermacher, quantized_by, tags

base_model	language	library_name	license	mradermacher	quantized_by	tags
Gille/StrangeMerges_51-7B-dare_ties	en	transformers	apache-2.0	readme_rev 1	mradermacher	merge mergekit lazymergekit WizardLM/WizardMath-7B-V1.1 Kukedlc/NeuralCoder-7b Weyaxi/Einstein-v4-7B 0-hero/Matter-0.1-Slim-7B-C-DPO Gille/StrangeMerges_42-7B-dare_ties

About

static quants of https://huggingface.co/Gille/StrangeMerges_51-7B-dare_ties

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

weighted/imatrix quants seem not to be available (by me) at this time. If they do not show up a week or so after the static ones, I have probably not planned for them. Feel free to request them by opening a Community Discussion.

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	2.8
GGUF	Q3_K_S	3.3
GGUF	Q3_K_M	3.6	lower quality
GGUF	Q3_K_L	3.9
GGUF	IQ4_XS	4.0
GGUF	Q4_K_S	4.2	fast, recommended
GGUF	Q4_K_M	4.5	fast, recommended
GGUF	Q5_K_S	5.1
GGUF	Q5_K_M	5.2
GGUF	Q6_K	6.0	very good quality
GGUF	Q8_0	7.8	fast, best quality
GGUF	f16	14.6	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.