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---
base_model:
- Himitsui/Kaiju-11B
- Sao10K/Fimbulvetr-11B-v2
- decapoda-research/Antares-11b-v2
- beberik/Nyxene-v3-11B
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
weighted/imatrix quants of https://huggingface.co/Steelskull/Umbra-v3-MoE-4x11b
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static quants are available at https://huggingface.co/mradermacher/Umbra-v3-MoE-4x11b-GGUF
## Usage
If you are unsure how to use GGUF files, refer to one of [TheBloke's
READMEs](https://huggingface.co/TheBloke/KafkaLM-70B-German-V0.1-GGUF) 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](https://huggingface.co/mradermacher/Umbra-v3-MoE-4x11b-i1-GGUF/resolve/main/Umbra-v3-MoE-4x11b.i1-IQ1_S.gguf) | i1-IQ1_S | 7.7 | for the desperate |
| [GGUF](https://huggingface.co/mradermacher/Umbra-v3-MoE-4x11b-i1-GGUF/resolve/main/Umbra-v3-MoE-4x11b.i1-IQ2_XXS.gguf) | i1-IQ2_XXS | 9.8 | |
| [GGUF](https://huggingface.co/mradermacher/Umbra-v3-MoE-4x11b-i1-GGUF/resolve/main/Umbra-v3-MoE-4x11b.i1-IQ2_XS.gguf) | i1-IQ2_XS | 10.9 | |
| [GGUF](https://huggingface.co/mradermacher/Umbra-v3-MoE-4x11b-i1-GGUF/resolve/main/Umbra-v3-MoE-4x11b.i1-IQ2_S.gguf) | i1-IQ2_S | 11.1 | |
| [GGUF](https://huggingface.co/mradermacher/Umbra-v3-MoE-4x11b-i1-GGUF/resolve/main/Umbra-v3-MoE-4x11b.i1-IQ2_M.gguf) | i1-IQ2_M | 12.2 | |
| [GGUF](https://huggingface.co/mradermacher/Umbra-v3-MoE-4x11b-i1-GGUF/resolve/main/Umbra-v3-MoE-4x11b.i1-Q2_K.gguf) | i1-Q2_K | 13.4 | IQ3_XXS probably better |
| [GGUF](https://huggingface.co/mradermacher/Umbra-v3-MoE-4x11b-i1-GGUF/resolve/main/Umbra-v3-MoE-4x11b.i1-IQ3_XXS.gguf) | i1-IQ3_XXS | 14.2 | fast, lower quality |
| [GGUF](https://huggingface.co/mradermacher/Umbra-v3-MoE-4x11b-i1-GGUF/resolve/main/Umbra-v3-MoE-4x11b.i1-IQ3_XS.gguf) | i1-IQ3_XS | 14.9 | |
| [GGUF](https://huggingface.co/mradermacher/Umbra-v3-MoE-4x11b-i1-GGUF/resolve/main/Umbra-v3-MoE-4x11b.i1-IQ3_S.gguf) | i1-IQ3_S | 15.8 | fast, beats Q3_K* |
| [GGUF](https://huggingface.co/mradermacher/Umbra-v3-MoE-4x11b-i1-GGUF/resolve/main/Umbra-v3-MoE-4x11b.i1-IQ3_M.gguf) | i1-IQ3_M | 16.1 | |
| [GGUF](https://huggingface.co/mradermacher/Umbra-v3-MoE-4x11b-i1-GGUF/resolve/main/Umbra-v3-MoE-4x11b.i1-Q3_K_M.gguf) | i1-Q3_K_M | 17.5 | IQ3_S probably better |
| [GGUF](https://huggingface.co/mradermacher/Umbra-v3-MoE-4x11b-i1-GGUF/resolve/main/Umbra-v3-MoE-4x11b.i1-Q4_K_M.gguf) | i1-Q4_K_M | 22.1 | fast, medium 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
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