README.md

metadata

base_model:
  - paulml/OmniBeagleSquaredMBX-v3-7B
  - nlpguy/AlloyIngotNeoX
  - Gille/StrangeMerges_21-7B-slerp
  - Kukedlc/Jupiter-k-7B-slerp
  - Kukedlc/NeuralSirKrishna-7b
exported_from: Kukedlc/Neural-4-ARC-7b
language:
  - en
library_name: transformers
license: apache-2.0
quantized_by: mradermacher
tags:
  - merge
  - mergekit
  - lazymergekit
  - paulml/OmniBeagleSquaredMBX-v3-7B
  - nlpguy/AlloyIngotNeoX
  - Gille/StrangeMerges_21-7B-slerp
  - Kukedlc/Jupiter-k-7B-slerp
  - Kukedlc/NeuralSirKrishna-7b

About

static quants of https://huggingface.co/Kukedlc/Neural-4-ARC-7b

weighted/imatrix quants seem not to be available (by me) at this time. If they do not show up a week or so after the static ones, I have probably not planned for them. Feel free to request them by opening a Community Discussion.

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	Q3_K_M	3.8	lower quality
GGUF	Q4_K_S	4.4	fast, recommended

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

And here are Artefact2's thoughts on the matter: https://gist.github.com/Artefact2/b5f810600771265fc1e39442288e8ec9

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.