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 | IQ4_XS | 8.8 | |
| GGUF | Q4_K_S | 9.2 | fast, recommended |
| GGUF | Q4_K_M | 9.7 | fast, recommended |
| GGUF | Q5_K_S | 11.1 | |
| GGUF | Q5_K_M | 11.4 | |
| GGUF | Q6_K | 13.2 | very good quality |
| GGUF | Q8_0 | 17.1 | fast, best quality |
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
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.