Aura-8B-i1-GGUF / README.md
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metadata
base_model: AuraIndustries/Aura-8B
datasets:
  - FourOhFour/RP_Phase
  - Nitral-AI/Cybersecurity-ShareGPT
  - Nitral-AI/Medical_Instruct-ShareGPT
  - Nitral-AI/Olympiad_Math-ShareGPT
  - NewEden/Claude-Instruct-5K
  - lodrick-the-lafted/kalo-opus-instruct-3k-filtered
  - Nitral-AI/Creative_Writing-ShareGPT
  - jeiku/Writing
  - anthracite-core/full-opus-chosen-hermes-rejected-kto-v1
language:
  - en
library_name: transformers
license: apache-2.0
quantized_by: mradermacher

About

weighted/imatrix quants of https://huggingface.co/AuraIndustries/Aura-8B

static quants are available at https://huggingface.co/mradermacher/Aura-8B-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 3.3 IQ3_XXS probably better
GGUF i1-IQ3_XXS 3.4 lower quality
GGUF i1-IQ3_M 3.9
GGUF i1-Q3_K_M 4.1 IQ3_S probably better
GGUF i1-Q4_K_S 4.8 optimal size/speed/quality

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.