metadata
base_model:
- moreh/MoMo-70B-lora-1.8.6-DPO
- binbi/MoMo-70B-V1.2_1
language:
- en
library_name: transformers
license: apache-2.0
quantized_by: mradermacher
tags:
- merge
- mergekit
- lazymergekit
- moreh/MoMo-70B-lora-1.8.6-DPO
- binbi/MoMo-70B-V1.2_1
About
static quants of https://huggingface.co/SF-Foundation/SF-72B-V1.8.6-V1.2
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 | 28.6 | |
GGUF | Q3_K_S | 33.1 | |
GGUF | Q3_K_M | 36.8 | lower quality |
GGUF | Q3_K_L | 40.0 | |
GGUF | Q4_K_S | 42.8 | fast, medium quality |
GGUF | Q4_K_M | 45.3 | fast, medium quality |
PART 1 PART 2 | Q5_K_S | 51.4 | |
PART 1 PART 2 | Q5_K_M | 52.9 | |
PART 1 PART 2 | Q6_K | 60.9 | very good quality |
PART 1 PART 2 | Q8_0 | 78.1 | 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.