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mradermacher/LLaMA2-13B-Tiefighter-i1-GGUF

sourceHugging Facellama2updated 2y agoView on Hugging Face

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Model Card

weighted/imatrix quants of https://huggingface.co/KoboldAI/LLaMA2-13B-Tiefighter

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.

(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	3.2	for the desperate
GGUF	i1-IQ1_M	3.2	mostly desperate
GGUF	i1-IQ2_XXS	3.9
GGUF	i1-IQ2_XS	4.2
GGUF	i1-IQ2_S	4.5
GGUF	i1-IQ2_M	4.8
GGUF	i1-Q2_K	5.1	IQ3_XXS probably better
GGUF	i1-IQ3_XXS	5.3	lower quality
GGUF	i1-IQ3_XS	5.7
GGUF	i1-IQ3_S	6.0	beats Q3_K*
GGUF	i1-Q3KS	6.0	IQ3_XS probably better
GGUF	i1-IQ3_M	6.3
GGUF	i1-Q3KM	6.6	IQ3_S probably better
GGUF	i1-IQ4_XS	7.1
GGUF	i1-Q3KL	7.2	IQ3_M probably better
GGUF	i1-Q4_0	7.5	fast, low quality
GGUF	i1-Q4KS	7.7	optimal size/speed/quality
GGUF	i1-Q4KM	8.2	fast, recommended
GGUF	i1-Q5KS	9.3
GGUF	i1-Q5KM	9.5
GGUF	i1-Q6_K	10.8	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

See https://huggingface.co/mradermacher/model_requests for some answers to questions you might have and/or if you want some other model quantized.

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.