base_model: OpenBuddy/openbuddy-qwen2.5llamaify-14b-v23.3-200k
language:
- zh
- en
- fr
- de
- ja
- ko
- it
- fi
library_name: transformers
license: apache-2.0
quantized_by: mradermacher
tags:
- llamaify
- qwen2.5
About
static quants of https://huggingface.co/OpenBuddy/openbuddy-qwen2.5llamaify-14b-v23.3-200k
weighted/imatrix quants are available at https://huggingface.co/mradermacher/openbuddy-qwen2.5llamaify-14b-v23.3-200k-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 | 5.9 | |
GGUF | Q3_K_S | 6.8 | |
GGUF | Q3_K_M | 7.4 | lower quality |
GGUF | Q3_K_L | 8.0 | |
GGUF | IQ4_XS | 8.3 | |
GGUF | Q4_K_S | 8.7 | fast, recommended |
GGUF | Q4_K_M | 9.1 | fast, recommended |
GGUF | Q5_K_S | 10.4 | |
GGUF | Q5_K_M | 10.6 | |
GGUF | Q6_K | 12.2 | very good quality |
GGUF | Q8_0 | 15.8 | 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.