About

weighted/imatrix quants of https://huggingface.co/Dogge/llama-3-70B-instruct-uncensored

No more quants are incoming, as llama.cpp crashes when generating them.

static quants are available at https://huggingface.co/mradermacher/llama-3-70B-instruct-uncensored-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 26.5 IQ3_XXS probably better
GGUF i1-Q3_K_S 31.0 IQ3_XS probably better
GGUF i1-Q3_K_M 34.4 IQ3_S probably better
GGUF i1-Q3_K_L 37.2 IQ3_M probably better
GGUF i1-IQ4_XS 38.0
GGUF i1-Q4_K_S 40.4 optimal size/speed/quality
GGUF i1-Q4_K_M 42.6 fast, recommended
GGUF i1-Q5_K_S 48.8
GGUF i1-Q5_K_M 50.1
PART 1 PART 2 i1-Q6_K 58.0 practically like static Q6_K

Here is a handy graph by ikawrakow comparing some lower-quality quant types (lower is better):

image.png

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.

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GGUF
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70.6B params
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llama

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