base_model: OmnicromsBrain/NeuralStar_AlphaWriter_4x7b
language:
- en
library_name: transformers
license: apache-2.0
quantized_by: mradermacher
tags:
- moe
- frankenmoe
- merge
- mergekit
- lazymergekit
- mlabonne/AlphaMonarch-7B
- FPHam/Karen_TheEditor_V2_STRICT_Mistral_7B
- SanjiWatsuki/Kunoichi-DPO-v2-7B
- OmnicromsBrain/NeuralStar-7b-Lazy
About
static quants of https://huggingface.co/OmnicromsBrain/NeuralStar_AlphaWriter_4x7b
weighted/imatrix quants are available at https://huggingface.co/mradermacher/NeuralStar_AlphaWriter_4x7b-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 | 8.9 | |
| GGUF | IQ3_XS | 10.0 | |
| GGUF | Q3_K_S | 10.5 | |
| GGUF | IQ3_S | 10.6 | beats Q3_K* |
| GGUF | IQ3_M | 10.7 | |
| GGUF | Q3_K_M | 11.7 | lower quality |
| GGUF | Q3_K_L | 12.6 | |
| GGUF | IQ4_XS | 13.1 | |
| GGUF | Q4_K_S | 13.8 | fast, recommended |
| GGUF | Q4_K_M | 14.7 | fast, recommended |
| GGUF | Q5_K_S | 16.7 | |
| GGUF | Q5_K_M | 17.2 | |
| GGUF | Q6_K | 19.9 | very good quality |
| GGUF | Q8_0 | 25.8 | 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.