File size: 4,493 Bytes
4337c1f 145eea6 4337c1f bdd7436 4337c1f a97490e 4337c1f a97490e 4337c1f 145eea6 4337c1f |
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 |
---
base_model: Steelskull/Lumosia-v2-MoE-4x10.7
language:
- en
library_name: transformers
license: apache-2.0
quantized_by: mradermacher
tags:
- Solar Moe
- Solar
- Lumosia
---
## About
weighted/imatrix quants of https://huggingface.co/Steelskull/Lumosia-v2-MoE-4x10.7
<!-- provided-files -->
static quants are available at https://huggingface.co/mradermacher/Lumosia-v2-MoE-4x10.7-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/Lumosia-v2-MoE-4x10.7-i1-GGUF/resolve/main/Lumosia-v2-MoE-4x10.7.i1-IQ1_S.gguf) | i1-IQ1_S | 7.7 | for the desperate |
| [GGUF](https://huggingface.co/mradermacher/Lumosia-v2-MoE-4x10.7-i1-GGUF/resolve/main/Lumosia-v2-MoE-4x10.7.i1-IQ2_XXS.gguf) | i1-IQ2_XXS | 9.8 | |
| [GGUF](https://huggingface.co/mradermacher/Lumosia-v2-MoE-4x10.7-i1-GGUF/resolve/main/Lumosia-v2-MoE-4x10.7.i1-IQ2_XS.gguf) | i1-IQ2_XS | 10.9 | |
| [GGUF](https://huggingface.co/mradermacher/Lumosia-v2-MoE-4x10.7-i1-GGUF/resolve/main/Lumosia-v2-MoE-4x10.7.i1-IQ2_S.gguf) | i1-IQ2_S | 11.1 | |
| [GGUF](https://huggingface.co/mradermacher/Lumosia-v2-MoE-4x10.7-i1-GGUF/resolve/main/Lumosia-v2-MoE-4x10.7.i1-IQ2_M.gguf) | i1-IQ2_M | 12.2 | |
| [GGUF](https://huggingface.co/mradermacher/Lumosia-v2-MoE-4x10.7-i1-GGUF/resolve/main/Lumosia-v2-MoE-4x10.7.i1-Q2_K.gguf) | i1-Q2_K | 13.4 | IQ3_XXS probably better |
| [GGUF](https://huggingface.co/mradermacher/Lumosia-v2-MoE-4x10.7-i1-GGUF/resolve/main/Lumosia-v2-MoE-4x10.7.i1-IQ3_XXS.gguf) | i1-IQ3_XXS | 14.2 | lower quality |
| [GGUF](https://huggingface.co/mradermacher/Lumosia-v2-MoE-4x10.7-i1-GGUF/resolve/main/Lumosia-v2-MoE-4x10.7.i1-IQ3_XS.gguf) | i1-IQ3_XS | 14.9 | |
| [GGUF](https://huggingface.co/mradermacher/Lumosia-v2-MoE-4x10.7-i1-GGUF/resolve/main/Lumosia-v2-MoE-4x10.7.i1-Q3_K_S.gguf) | i1-Q3_K_S | 15.8 | IQ3_XS probably better |
| [GGUF](https://huggingface.co/mradermacher/Lumosia-v2-MoE-4x10.7-i1-GGUF/resolve/main/Lumosia-v2-MoE-4x10.7.i1-IQ3_S.gguf) | i1-IQ3_S | 15.8 | beats Q3_K* |
| [GGUF](https://huggingface.co/mradermacher/Lumosia-v2-MoE-4x10.7-i1-GGUF/resolve/main/Lumosia-v2-MoE-4x10.7.i1-IQ3_M.gguf) | i1-IQ3_M | 16.1 | |
| [GGUF](https://huggingface.co/mradermacher/Lumosia-v2-MoE-4x10.7-i1-GGUF/resolve/main/Lumosia-v2-MoE-4x10.7.i1-Q3_K_M.gguf) | i1-Q3_K_M | 17.5 | IQ3_S probably better |
| [GGUF](https://huggingface.co/mradermacher/Lumosia-v2-MoE-4x10.7-i1-GGUF/resolve/main/Lumosia-v2-MoE-4x10.7.i1-Q3_K_L.gguf) | i1-Q3_K_L | 19.0 | IQ3_M probably better |
| [GGUF](https://huggingface.co/mradermacher/Lumosia-v2-MoE-4x10.7-i1-GGUF/resolve/main/Lumosia-v2-MoE-4x10.7.i1-IQ4_XS.gguf) | i1-IQ4_XS | 19.5 | |
| [GGUF](https://huggingface.co/mradermacher/Lumosia-v2-MoE-4x10.7-i1-GGUF/resolve/main/Lumosia-v2-MoE-4x10.7.i1-Q4_K_S.gguf) | i1-Q4_K_S | 20.8 | optimal size/speed/quality |
| [GGUF](https://huggingface.co/mradermacher/Lumosia-v2-MoE-4x10.7-i1-GGUF/resolve/main/Lumosia-v2-MoE-4x10.7.i1-Q4_K_M.gguf) | i1-Q4_K_M | 22.1 | fast, recommended |
| [GGUF](https://huggingface.co/mradermacher/Lumosia-v2-MoE-4x10.7-i1-GGUF/resolve/main/Lumosia-v2-MoE-4x10.7.i1-Q5_K_S.gguf) | i1-Q5_K_S | 25.1 | |
| [GGUF](https://huggingface.co/mradermacher/Lumosia-v2-MoE-4x10.7-i1-GGUF/resolve/main/Lumosia-v2-MoE-4x10.7.i1-Q5_K_M.gguf) | i1-Q5_K_M | 25.9 | |
| [GGUF](https://huggingface.co/mradermacher/Lumosia-v2-MoE-4x10.7-i1-GGUF/resolve/main/Lumosia-v2-MoE-4x10.7.i1-Q6_K.gguf) | i1-Q6_K | 29.9 | practically like static Q6_K |
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](https://www.nethype.de/), for letting
me use its servers and providing upgrades to my workstation to enable
this work in my free time.
<!-- end -->
|