mradermacher/dbrx-instruct-i1-GGUF

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### DBRX Terms of Use
Use of DBRX is governed by the Databricks Open Model License and the Databricks Open Model Acceptable Use Policy.
language:

• en

library_name: transformers
quantized_by: mradermacher

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About

weighted/imatrix quants of https://huggingface.co/alpindale/dbrx-instruct

static quants are available at https://huggingface.co/mradermacher/dbrx-instruct-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	27.0	for the desperate
GGUF	i1-IQ1_M	29.9	mostly desperate
GGUF	i1-IQ2_XXS	34.7
GGUF	i1-IQ2_XS	38.6
GGUF	i1-IQ2_S	39.4
GGUF	i1-IQ2_M	43.3
GGUF	i1-Q2K	48.0	IQ3XXS probably better
PART 1 PART 2	i1-IQ3_XXS	50.8	lower quality
PART 1 PART 2	i1-IQ3_XS	53.9
PART 1 PART 2	i1-IQ3S	56.9	beats Q3K*
PART 1 PART 2	i1-Q3KS	56.9	IQ3_XS probably better
PART 1 PART 2	i1-IQ3_M	58.1
PART 1 PART 2	i1-Q3KM	63.2	IQ3_S probably better
PART 1 PART 2	i1-Q3KL	68.5	IQ3_M probably better
PART 1 PART 2	i1-IQ4_XS	70.2
PART 1 PART 2	i1-Q4_0	74.6	fast, low quality
PART 1 PART 2	i1-Q4KS	75.0	optimal size/speed/quality
PART 1 PART 2	i1-Q4KM	80.0	fast, recommended
PART 1 PART 2	i1-Q5KS	90.7
PART 1 PART 2	i1-Q5KM	93.7
PART 1 PART 2 PART 3	i1-Q6K	108.1	practically like static Q6K

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.