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metadata
base_model: TeeZee/GALAXY-16B-v1.0
datasets:
  - Intel/orca_dpo_pairs
  - athirdpath/DPO_Pairs-Roleplay-Alpaca-NSFW
  - Open-Orca/SlimOrca
  - MinervaAI/Aesir-Preview
  - allenai/ultrafeedback_binarized_cleaned
language:
  - en
library_name: transformers
license: apache-2.0
quantized_by: mradermacher
tags:
  - not-for-all-audiences

About

static quants of https://huggingface.co/TeeZee/GALAXY-16B-v1.0

weighted/imatrix quants are available at https://huggingface.co/mradermacher/GALAXY-16B-v1.0-i1-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 Q2_K 6.0
GGUF Q3_K_S 7.0
GGUF Q3_K_M 7.8 lower quality
GGUF Q3_K_L 8.5
GGUF Q4_K_S 9.2 fast, recommended
GGUF Q4_K_M 9.7 fast, recommended
GGUF Q6_K 13.2 very good 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.