base_model: prithivMLmods/Qwen3.6-27B-Uncensored-Aggressive
datasets:
- prithivMLmods/harm_bench
language: - en
library_name: transformers
license: apache-2.0
mradermacher:
readme_rev: 1
quantized_by: mradermacher
tags: - text-generation-inference
- uncensored
- abliterated
- unfiltered
- unredacted
- refusal-ablated
- vllm
- pytorch
- bf16
- max
- alignment-modified
- reasoning
- agent
About
static quants of https://huggingface.co/prithivMLmods/Qwen3.6-27B-Uncensored-Aggressive
For a convenient overview and download list, visit our model page for this model.
weighted/imatrix quants are available at https://huggingface.co/mradermacher/Qwen3.6-27B-Uncensored-Aggressive-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 | mmproj-Q8_0 | 0.7 | multi-modal supplement |
| GGUF | mmproj-f16 | 1.0 | multi-modal supplement |
| GGUF | Q2_K | 10.8 | |
| GGUF | Q3_K_S | 12.2 | |
| GGUF | Q3_K_M | 13.4 | lower quality |
| GGUF | Q3_K_L | 14.4 | |
| GGUF | IQ4_XS | 15.3 | |
| GGUF | Q4_K_S | 15.7 | fast, recommended |
| GGUF | Q4_K_M | 16.6 | fast, recommended |
| GGUF | Q5_K_S | 18.8 | |
| GGUF | Q5_K_M | 19.3 | |
| GGUF | Q6_K | 22.2 | very good quality |
| GGUF | Q8_0 | 28.7 | 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.