base_model: mlabonne/BigQwen2.5-125B-Instruct
language:
- en
library_name: transformers
license: other
license_link: https://huggingface.co/Qwen/Qwen2-72B-Instruct/blob/main/LICENSE
license_name: tongyi-qianwen
quantized_by: mradermacher
tags:
- mergekit
- merge
- lazymergekit
About
static quants of https://huggingface.co/mlabonne/BigQwen2.5-125B-Instruct
weighted/imatrix quants seem not to be available (by me) at this time. If they do not show up a week or so after the static ones, I have probably not planned for them. Feel free to request them by opening a Community Discussion.
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 |
|---|---|---|---|
| PART 1 PART 2 | Q2_K | 51.0 | |
| PART 1 PART 2 | IQ3_XS | 56.3 | |
| PART 1 PART 2 | Q3_K_S | 59.0 | |
| PART 1 PART 2 | IQ3_S | 59.1 | beats Q3_K* |
| PART 1 PART 2 | IQ3_M | 60.9 | |
| PART 1 PART 2 | Q3_K_M | 64.7 | lower quality |
| PART 1 PART 2 | Q3_K_L | 68.1 | |
| PART 1 PART 2 | Q4_K_S | 75.5 | fast, recommended |
| PART 1 PART 2 | Q4_K_M | 81.7 | fast, recommended |
| PART 1 PART 2 | Q5_K_S | 88.6 | |
| PART 1 PART 2 | Q5_K_M | 94.0 | |
| PART 1 PART 2 PART 3 | Q6_K | 111.2 | very good quality |
| PART 1 PART 2 PART 3 | Q8_0 | 133.3 | 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.