Files

55 lines
2.7 KiB
Markdown
Raw Permalink Normal View History

---
tags:
- chat
base_model: Qwen/Qwen3-4B-Instruct-2507
pipeline_tag: text-generation
library_name: mlx
---
# JOSIEFIED Model Family
![Logo/JPG](josiefied-gabliterated.png)
The **JOSIEFIED** model family represents a series of highly advanced language models built upon renowned architectures such as Alibabas Qwen2/2.5/3, Googles Gemma3, and Metas LLaMA3/4. Covering sizes from 0.5B to 32B parameters, these models have been significantly modified (*“gabliterated”*) and further fine-tuned to **maximize uncensored behavior** without compromising tool usage or instruction-following abilities.
Despite their rebellious spirit, the JOSIEFIED models often outperform their base counterparts on standard benchmarks — delivering both raw power and utility.
These models are intended for advanced users who require unrestricted, high-performance language generation.
## Model Card for Goekdeniz-Guelmez/Josiefied-Qwen3-4B-Instruct-2507-gabliterated-v2
### Model Description
Introducing *Josiefied-Qwen3-4B-Instruct-2507-gabliterated-v2*, a new addition to the JOSIEFIED family — fine-tuned and gabliterated with a focus on openness and instruction alignment. This one marks my new dataset, which gives Josie more personality and a little humor.
### Gabliteration
With this model series, I introduce the first Gabliteration, a novel neural weight modification technique that advances beyond traditional abliteration methods through adaptive multi-directional projections with regularized layer selection.
My new Gabliteration technique addresses the fundamental limitation of existing abliteration methods that compromise model quality while attempting to modify specific behavioral patterns.
#### Technical Background
Building upon the foundational work of Arditi et al. (2024) on single-direction abliteration, Gabliteration extends to a comprehensive multi-directional framework with theoretical guarantees. My method employs singular value decomposition on difference matrices between harmful and harmless prompt representations to extract multiple refusal directions.
### Quantisations
- [GGUF (mradermacher)](https://huggingface.co/mradermacher/)
- [i1 GGUF (mradermacher)](https://huggingface.co/mradermacher/)
- [AWQ (warshanks)](https://huggingface.co/warshanks/Josiefied-Qwen3-4B-Instruct-2507-gabliterated-v2-AWQ)
#### Ollama
```
not uploaded yet
```
- **Developed by:** Goekdeniz-Guelmez
- **Funded by:** Goekdeniz-Guelmez
- **Shared by:** Goekdeniz-Guelmez
- **Model type:** qwen3
- **Finetuned from model:** Qwen/Qwen3-4B-Instruct-2507
## Bias, Risks, and Limitations
This model has reduced safety filtering and may generate sensitive or controversial outputs.
Use responsibly and at your own risk.