mradermacher/aurelian-v0.5-70b-rope8-32K-fp16-i1-GGUF

About

weighted/imatrix quants of https://huggingface.co/grimulkan/aurelian-v0.5-70b-rope8-32K-fp16

No more quants will be forthcoming, as llama.cpp crashes, as usual.

static quants are available at https://huggingface.co/mradermacher/aurelian-v0.5-70b-rope8-32K-fp16-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-Q2_K	25.6	IQ3_XXS probably better
GGUF	i1-Q4_K_S	39.3	optimal size/speed/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.