datasets:
- ewof/koishi-instruct-metharme
exported_from: ewof/koishi-8x7b-qlora
language:
- en
library_name: transformers
quantized_by: mradermacher
About
static quants of https://huggingface.co/ewof/koishi-8x7b-qlora
weighted/imatrix quants are available at https://huggingface.co/mradermacher/koishi-8x7b-qlora-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 | IQ3_S | 20.5 | beats Q3_K* |
| GGUF | Q4_K_S | 26.8 | fast, recommended |
| GGUF | Q8_0 | 49.7 | 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.