How to use from the
Use from the
llama-cpp-python library
# !pip install llama-cpp-python

from llama_cpp import Llama

llm = Llama.from_pretrained(
	repo_id="mradermacher/XORTRON.CriminalComputing.Config.LARGE.XPRT2-i1-GGUF",
	filename="",
)
llm.create_chat_completion(
	messages = "No input example has been defined for this model task."
)

About

weighted/imatrix quants of https://huggingface.co/darkc0de/XORTRON.CriminalComputing.Config.LARGE.XPRT2

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

static quants are available at https://huggingface.co/mradermacher/XORTRON.CriminalComputing.Config.LARGE.XPRT2-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 imatrix 0.1 imatrix file (for creating your own quants)
GGUF i1-IQ1_S 27.3 for the desperate
GGUF i1-IQ1_M 29.7 mostly desperate
GGUF i1-IQ2_XXS 33.8
GGUF i1-IQ2_XS 37.4
GGUF i1-IQ2_S 39.8
GGUF i1-IQ2_M 43.1
GGUF i1-Q2_K_S 43.1 very low quality
GGUF i1-Q2_K 46.7 IQ3_XXS probably better
GGUF i1-IQ3_XXS 48.5 lower quality
GGUF i1-IQ3_XS 51.8
GGUF i1-Q3_K_S 54.5 IQ3_XS probably better
GGUF i1-IQ3_S 54.6 beats Q3_K*
GGUF i1-IQ3_M 56.9
GGUF i1-Q3_K_M 60.7 IQ3_S probably better
GGUF i1-Q3_K_L 66.2 IQ3_M probably better
GGUF i1-IQ4_XS 67.2
GGUF i1-Q4_0 71.1 fast, low quality
GGUF i1-Q4_K_S 71.3 optimal size/speed/quality
GGUF i1-Q4_K_M 75.0 fast, recommended
GGUF i1-Q4_1 78.6
GGUF i1-Q5_K_S 86.3
GGUF i1-Q5_K_M 88.4
PART 1 PART 2 PART 3 i1-Q6_K 102.7 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. 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.

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