---
base_model:
- trentmkelly/gpt-4o-distil-Llama-3.1-8B-Instruct
library_name: transformers
model_name: llama-3.1-8b-4o-final
tags:
- base_model:adapter:meta-llama/Llama-3.1-8B-Instruct
- dpo
- lora
- sft
- transformers
- trl
- heretic
- uncensored
- decensored
- abliterated
licence: license
pipeline_tag: text-generation
base_model_relation: finetune
---

This is a **gpt-4o-distil-Llama-3.1-8B-Instruct** fine-tune, produced through P-E-W's [Heretic](https://github.com/p-e-w/heretic) (v1.2.0) abliteration engine with [Magnitude-Preserving Orthogonal Ablation](https://github.com/p-e-w/heretic/pull/52) enabled.

---
<img src="https://img.shields.io/badge/RENEGADE_CHAPTER-PAPERWITCH-B85ADB?style=flat-square&labelColor=101010" align="right" width="300">

**Heretication Results**

| Score Metric | Value | Parameter | Value |
| :--- | :--- | :--- | :--- |
| **Refusals** | 7/100 | **direction_index** | per layer |
| **KL Divergence** | 0.0274  | **attn.o_proj.max_weight** | 1.88 |
| **Initial Refusals** | 98/100 | **attn.o_proj.max_weight_position** | 23.88 |
||| **attn.o_proj.min_weight** | 0.91 |
||| **attn.o_proj.min_weight_distance** | 17.00 |
||| **mlp.down_proj.max_weight** | 0.16 |
||| **mlp.down_proj.max_weight_position** | 14.31 |
||| **mlp.down_proj.min_weight** | 0.00 |
||| **mlp.down_proj.min_weight_distance** | 18.09 |

---
**Appendix**

> One-sentence system prompt.

<img src="gpt-4o-distil-Llama-3.1-8B-Instruct.gif" alt="PaCMAP projection"/>

```
 » [Trial  41] Refusals:  7/100, KL divergence: 0.0274
   [Trial 189] Refusals:  8/100, KL divergence: 0.0264
   [Trial  87] Refusals:  9/100, KL divergence: 0.0207
   [Trial  73] Refusals: 11/100, KL divergence: 0.0173
   [Trial  39] Refusals: 13/100, KL divergence: 0.0124
   [Trial 171] Refusals: 20/100, KL divergence: 0.0105
   [Trial  67] Refusals: 28/100, KL divergence: 0.0078
   [Trial  62] Refusals: 41/100, KL divergence: 0.0064
   [Trial 169] Refusals: 51/100, KL divergence: 0.0062
   [Trial  82] Refusals: 52/100, KL divergence: 0.0056
   [Trial  65] Refusals: 73/100, KL divergence: 0.0047
   [Trial 132] Refusals: 80/100, KL divergence: 0.0046
   [Trial  18] Refusals: 82/100, KL divergence: 0.0038
   [Trial 165] Refusals: 91/100, KL divergence: 0.0031
   [Trial 121] Refusals: 93/100, KL divergence: 0.0022
   [Trial 140] Refusals: 94/100, KL divergence: 0.0021
   [Trial 150] Refusals: 95/100, KL divergence: 0.0020
   [Trial 125] Refusals: 97/100, KL divergence: 0.0016
   [Trial 184] Refusals: 98/100, KL divergence: 0.0006
```


---
# Model Card for llama-3.1-8b-4o-final

This model is a fine-tuned version of [meta-llama/Llama-3.1-8B-Instruct](https://huggingface.co/meta-llama/Llama-3.1-8B-Instruct).
It has been trained using [TRL](https://github.com/huggingface/trl).

## Quick start

```python
from transformers import pipeline

question = "If you had a time machine, but could only go to the past or the future once and never return, which would you choose and why?"
generator = pipeline("text-generation", model="None", device="cuda")
output = generator([{"role": "user", "content": question}], max_new_tokens=128, return_full_text=False)[0]
print(output["generated_text"])
```

## Training procedure

[<img src="https://raw.githubusercontent.com/wandb/assets/main/wandb-github-badge-28.svg" alt="Visualize in Weights & Biases" width="150" height="24"/>](https://wandb.ai/trent-michael-kelly-g/huggingface/runs/dnx8m9jj) 


This model was trained with SFT.

### Framework versions

- PEFT 0.18.1
- TRL: 0.27.1
- Transformers: 5.0.0
- Pytorch: 2.9.0.dev20250708+cu128
- Datasets: 4.5.0
- Tokenizers: 0.22.2

## Citations



Cite TRL as:
    
```bibtex
@misc{vonwerra2022trl,
	title        = {{TRL: Transformer Reinforcement Learning}},
	author       = {Leandro von Werra and Younes Belkada and Lewis Tunstall and Edward Beeching and Tristan Thrush and Nathan Lambert and Shengyi Huang and Kashif Rasul and Quentin Gallou{\'e}dec},
	year         = 2020,
	journal      = {GitHub repository},
	publisher    = {GitHub},
	howpublished = {\url{https://github.com/huggingface/trl}}
}
```