metadata
base_model:
- mlabonne/NeuralBeagle14-7B
- FelixChao/WestSeverus-7B-DPO-v2
- jsfs11/TurdusTrixBeagle-DARETIES-7B
language:
- en
library_name: transformers
license: apache-2.0
quantized_by: mradermacher
tags:
- merge
- mergekit
- lazymergekit
- mlabonne/NeuralBeagle14-7B
- FelixChao/WestSeverus-7B-DPO-v2
- jsfs11/TurdusTrixBeagle-DARETIES-7B
About
static quants of https://huggingface.co/CultriX/CombinaTrix-7B
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 | 3.0 | |
| GGUF | Q3_K_S | 3.4 | |
| GGUF | Q3_K_M | 3.8 | lower quality |
| GGUF | Q3_K_L | 4.1 | |
| GGUF | Q4_K_S | 4.4 | fast, medium quality |
| GGUF | Q4_K_M | 4.6 | fast, medium quality |
| GGUF | Q5_K_S | 5.3 | |
| GGUF | Q5_K_M | 5.4 | |
| GGUF | Q6_K | 6.2 | very good quality |
| GGUF | Q8_0 | 7.9 | 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
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.