base_model: DavidAU/Qwen2.5-3X7B-CoderInstruct-OlympicCoder-MS-Next-Coder-25B-v1
language:
- en
library_name: transformers
license: apache-2.0
mradermacher:
readme_rev: 1
quantized_by: mradermacher
tags:
- merge
- programming
- code generation
- code
- codeqwen
- moe
- coding
- coder
- qwen2
- chat
- qwen
- qwen-coder
- mixture of experts
- qwen2moe
- 3X7B Shared.
About
static quants of https://huggingface.co/DavidAU/Qwen2.5-3X7B-CoderInstruct-OlympicCoder-MS-Next-Coder-25B-v1
For a convenient overview and download list, visit our model page for this model.
weighted/imatrix quants are available at https://huggingface.co/mradermacher/Qwen2.5-3X7B-CoderInstruct-OlympicCoder-MS-Next-Coder-25B-v1-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 | 9.3 | |
| GGUF | Q3_K_S | 10.9 | |
| GGUF | Q3_K_M | 12.0 | lower quality |
| GGUF | Q3_K_L | 13.0 | |
| GGUF | IQ4_XS | 13.5 | |
| GGUF | Q4_K_S | 14.3 | fast, recommended |
| GGUF | Q4_K_M | 15.1 | fast, recommended |
| GGUF | Q5_K_S | 17.2 | |
| GGUF | Q5_K_M | 17.7 | |
| GGUF | Q6_K | 20.4 | very good quality |
| GGUF | Q8_0 | 26.4 | 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.