datasets:
- wenbopan/Fusang-v1
- wenbopan/OpenOrca-zh-20k
exported_from: wenbopan/Faro-Yi-34B-200K
language:
- en
library_name: transformers
license: mit
quantized_by: mradermacher
About
weighted/imatrix quants of https://huggingface.co/wenbopan/Faro-Yi-34B-200K
This uses my "quarter" training set of 40k tokens as the model overflowed after 25k tokens with the standard set.
static quants are available at https://huggingface.co/mradermacher/Faro-Yi-34B-200K-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 | i1-Q2_K | 13.5 | IQ3_XXS probably better |
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.