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mradermacher/Babel-83B-Chat-i1-GGUF

sourceHugging Faceotherupdated 2y agoView on Hugging Face

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About

weighted/imatrix quants of https://huggingface.co/Tower-Babel/Babel-83B-Chat

static quants are available at https://huggingface.co/mradermacher/Babel-83B-Chat-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	26.0	for the desperate
GGUF	i1-IQ1_M	27.2	mostly desperate
GGUF	i1-IQ2_XXS	29.2
GGUF	i1-IQ2_XS	31.0
GGUF	i1-IQ2_S	32.0
GGUF	i1-IQ2_M	33.6
GGUF	i1-Q2KS	33.8	very low quality
GGUF	i1-Q2_K	34.1	IQ3_XXS probably better
GGUF	i1-IQ3_XXS	36.4	lower quality
GGUF	i1-IQ3_XS	37.5
GGUF	i1-Q3KS	39.3	IQ3_XS probably better
GGUF	i1-IQ3_S	39.4	beats Q3_K*
GGUF	i1-IQ3_M	40.6
GGUF	i1-Q3KM	43.1	IQ3_S probably better
GGUF	i1-Q3KL	45.3	IQ3_M probably better
GGUF	i1-IQ4_XS	45.5
GGUF	i1-Q4_0	47.4	fast, low quality
PART 1 PART 2	i1-Q4KS	50.2	optimal size/speed/quality
PART 1 PART 2	i1-Q4_1	52.4
PART 1 PART 2	i1-Q4KM	54.3	fast, recommended
PART 1 PART 2	i1-Q5KS	58.9
PART 1 PART 2	i1-Q5KM	62.4
PART 1 PART 2	i1-Q6_K	73.8	practically like static Q6_K

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. 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.