base_model: huihui-ai/Qwen2.5-7B-Instruct-abliterated-v2
language:
- zho
- eng
- fra
- spa
- por
- deu
- ita
- rus
- jpn
- kor
- vie
- tha
- ara
library_name: transformers
license: apache-2.0
license_link: https://huggingface.co/huihui-ai/Qwen2.5-7B-Instruct-abliterated-v2/blob/main/LICENSE
quantized_by: mradermacher
tags: - chat
- abliterated
- uncensored
About
static quants of https://huggingface.co/huihui-ai/Qwen2.5-7B-Instruct-abliterated-v2
weighted/imatrix quants are available at https://huggingface.co/mradermacher/Qwen2.5-7B-Instruct-abliterated-v2-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 | 3.1 | |
| GGUF | IQ3_XS | 3.4 | |
| GGUF | Q3_K_S | 3.6 | |
| GGUF | IQ3_S | 3.6 | beats Q3_K* |
| GGUF | IQ3_M | 3.7 | |
| GGUF | Q3_K_M | 3.9 | lower quality |
| GGUF | Q3_K_L | 4.2 | |
| GGUF | IQ4_XS | 4.4 | |
| GGUF | Q4_K_S | 4.6 | fast, recommended |
| GGUF | Q4_K_M | 4.8 | fast, recommended |
| GGUF | Q5_K_S | 5.4 | |
| GGUF | Q5_K_M | 5.5 | |
| GGUF | Q6_K | 6.4 | very good quality |
| GGUF | Q8_0 | 8.2 | fast, best quality |
| GGUF | f16 | 15.3 | 16 bpw, overkill |
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.