base_model: DisOOM/Yi-70B-200k-RPMerge-Franken
language:
- en
- chi
library_name: transformers
license: other
license_link: https://huggingface.co/01-ai/Yi-34B/blob/main/LICENSE
license_name: yi-license
quantized_by: mradermacher
tags:
- merge
- mergekit
- Yi
- chat
- conversational
About
static quants of https://huggingface.co/DisOOM/Yi-70B-200k-RPMerge-Franken
weighted/imatrix quants are available at https://huggingface.co/mradermacher/Yi-70B-200k-RPMerge-Franken-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 | Q2_K | 26.5 | |
GGUF | Q3_K_S | 30.9 | |
GGUF | Q3_K_M | 34.5 | lower quality |
GGUF | Q3_K_L | 37.6 | |
GGUF | IQ4_XS | 38.6 | |
GGUF | Q4_K_S | 40.6 | fast, recommended |
GGUF | Q4_K_M | 42.7 | fast, recommended |
GGUF | Q5_K_S | 49.1 | |
PART 1 PART 2 | Q5_K_M | 50.4 | |
PART 1 PART 2 | Q6_K | 58.5 | very good quality |
PART 1 PART 2 | Q8_0 | 75.8 | 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
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, for letting me use its servers and providing upgrades to my workstation to enable this work in my free time. Additional thanks to @nicoboss for giving me access to his private supercomputer, enabling me to provide many more imatrix quants, at much higher quality, than I would otherwise be able to.