base_model: DavidAU/Qwen3.8-27B-TWIN-TURBO-Fable-Cold-Fusion-709-L-Uncensored
datasets:
- DavidAU/Polar-STRICT-Datasets
- DavidAU/F451-STRICT-Datasets
- DavidAU/THE-DECKARD-Datasets
language: - en
library_name: transformers
license: apache-2.0
mradermacher:
readme_rev: 1
quantized_by: mradermacher
tags: - heretic
- qwen3_8
- qwen3_6
- uncensored
- finetune
- Cold Fusion
- GAIN Training
- Multi-stage tuning
- all use cases
- unsloth
About
static quants of https://huggingface.co/DavidAU/Qwen3.8-27B-TWIN-TURBO-Fable-Cold-Fusion-709-L-Uncensored
For a convenient overview and download list, visit our model page for this model.
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 |
|---|---|---|---|
| GGUF | mmproj-Q8_0 | 0.7 | multi-modal supplement |
| GGUF | mmproj-f16 | 1.0 | multi-modal supplement |
| GGUF | Q2_K | 11.0 | |
| GGUF | Q4_K_S | 15.9 | fast, recommended |
| GGUF | Q6_K | 22.5 | very good quality |
| GGUF | Q8_0 | 29.1 | 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.