mradermacher/bloomz-7b1-mt-i1-GGUF

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base_model: bigscience/bloomz-7b1-mt datasets:

• bigscience/xP3mt

language:

• ak
• ar
• as
• bm
• bn
• ca
• code
• en
• es
• eu
• fon
• fr
• gu
• hi
• id
• ig
• ki
• kn
• lg
• ln
• ml
• mr
• ne
• nso
• ny
• or
• pa
• pt
• rn
• rw
• sn
• st
• sw
• ta
• te
• tn
• ts
• tum
• tw
• ur
• vi
• wo
• xh
• yo
• zh
• zu

library_name: transformers license: bigscience-bloom-rail-1.0 quantized_by: mradermacher

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About

weighted/imatrix quants of https://huggingface.co/bigscience/bloomz-7b1-mt

static quants are available at https://huggingface.co/mradermacher/bloomz-7b1-mt-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	2.4	for the desperate
GGUF	i1-IQ1_M	2.5	mostly desperate
GGUF	i1-IQ2_XXS	2.7
GGUF	i1-IQ2_XS	2.9
GGUF	i1-IQ2_S	3.1
GGUF	i1-IQ2_M	3.3
GGUF	i1-Q2K_S	3.3	very low quality
GGUF	i1-Q2K	3.5	IQ3XXS probably better
GGUF	i1-IQ3_XXS	3.6	lower quality
GGUF	i1-IQ3_XS	3.9
GGUF	i1-IQ3S	4.0	beats Q3K*
GGUF	i1-Q3KS	4.0	IQ3XS probably better
GGUF	i1-IQ3_M	4.3
GGUF	i1-Q3KM	4.5	IQ3S probably better
GGUF	i1-IQ4_XS	4.7
GGUF	i1-Q3KL	4.8	IQ3M probably better
GGUF	i1-IQ4NL	4.9	prefer IQ4XS
GGUF	i1-Q4_0	5.0	fast, low quality
GGUF	i1-Q4K_S	5.0	optimal size/speed/quality
GGUF	i1-Q4K_M	5.4	fast, recommended
GGUF	i1-Q4_1	5.4
GGUF	i1-Q5K_S	5.8
GGUF	i1-Q5K_M	6.1
GGUF	i1-Q6K	6.8	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.