exported_from: Weyaxi/Bagel-Hermes-2x34B
language:
- en
library_name: transformers
license: other
license_link: https://huggingface.co/01-ai/Yi-34B-200K/blob/main/LICENSE
license_name: yi-license
quantized_by: mradermacher
tags:
- yi
- moe
About
weighted/imatrix quants of https://huggingface.co/Weyaxi/Bagel-Hermes-2x34B
static quants are available at https://huggingface.co/mradermacher/Bagel-Hermes-2x34B-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-IQ2_M | 20.5 | |
| GGUF | i1-Q2_K | 22.5 | IQ3_XXS probably better |
| GGUF | i1-IQ3_XXS | 23.6 | lower quality |
| GGUF | i1-Q3_K_S | 26.4 | IQ3_XS probably better |
| GGUF | i1-Q3_K_M | 29.3 | IQ3_S probably better |
| GGUF | i1-Q3_K_L | 31.9 | IQ3_M probably better |
| GGUF | i1-IQ4_XS | 32.6 | |
| GGUF | i1-Q4_K_S | 34.7 | optimal size/speed/quality |
| GGUF | i1-Q4_K_M | 36.8 | fast, recommended |
| GGUF | i1-Q5_K_S | 42.0 | |
| GGUF | i1-Q6_K | 50.0 | 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
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.