base_model: mlabonne/BigQwen2.5-Echo-47B-Instruct
language:
- en
library_name: transformers
license: apache-2.0
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-Echo-47B-Instruct
weighted/imatrix quants are available at https://huggingface.co./mradermacher/BigQwen2.5-Echo-47B-Instruct-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 | 17.8 | |
| GGUF | IQ3_XS | 19.8 | |
| GGUF | Q3_K_S | 20.8 | |
| GGUF | IQ3_S | 20.8 | beats Q3_K* |
| GGUF | IQ3_M | 21.4 | |
| GGUF | Q3_K_M | 23.0 | lower quality |
| GGUF | Q3_K_L | 25.0 | |
| GGUF | IQ4_XS | 25.8 | |
| GGUF | Q4_K_S | 27.2 | fast, recommended |
| GGUF | Q4_K_M | 28.7 | fast, recommended |
| GGUF | Q5_K_S | 32.8 | |
| GGUF | Q5_K_M | 33.7 | |
| GGUF | Q6_K | 39.0 | very good quality |
| PART 1 PART 2 | Q8_0 | 50.5 | 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.