base_model: Steelskull/Umbra-v3-MoE-4x11b-2ex
language:
- en
library_name: transformers
license: apache-2.0
quantized_by: mradermacher
tags:
- moe
- frankenmoe
- merge
- mergekit
- Himitsui/Kaiju-11B
- Sao10K/Fimbulvetr-11B-v2
- decapoda-research/Antares-11b-v2
- beberik/Nyxene-v3-11B
About
static quants of https://huggingface.co/Steelskull/Umbra-v3-MoE-4x11b-2ex
weighted/imatrix quants are available at https://huggingface.co/mradermacher/Umbra-v3-MoE-4x11b-2ex-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 | 13.3 | |
| GGUF | IQ3_XS | 14.9 | |
| GGUF | Q3_K_S | 15.7 | |
| GGUF | IQ3_S | 15.7 | beats Q3_K* |
| GGUF | IQ3_M | 16.0 | |
| GGUF | Q3_K_M | 17.4 | lower quality |
| GGUF | Q3_K_L | 18.8 | |
| GGUF | IQ4_XS | 19.6 | |
| GGUF | Q4_K_S | 20.6 | fast, recommended |
| GGUF | Q4_K_M | 21.9 | fast, recommended |
| GGUF | Q5_K_S | 24.9 | |
| GGUF | Q5_K_M | 25.7 | |
| GGUF | Q6_K | 29.7 | very good quality |
| GGUF | Q8_0 | 38.5 | 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.