---
language:
- en
- de
- fr
- it
- pt
- hi
- es
- th
library_name: transformers
pipeline_tag: text-generation
tags:
- facebook
- meta
- pytorch
- llama
- llama-3
- heretic
- uncensored
- decensored
- abliterated
license: llama3.2
---

# Llama-3.2-1B-Instruct-heretic

A decensored variant of [meta-llama/Llama-3.2-1B-Instruct](https://huggingface.co/meta-llama/Llama-3.2-1B-Instruct), produced with [Heretic](https://github.com/p-e-w/heretic) v1.2.0 (directional ablation / "abliteration"). Refusal behavior is suppressed via targeted weight edits to the attention output and MLP down-projections rather than fine-tuning, so the base model's knowledge and instruction-following are left largely intact.

**Who this is for:** developers who want Meta's Llama-3.2 architecture without the refusal guardrails — for local agents, roleplay, research on alignment/refusal mechanics, or any use case blocked by RLHF-era over-refusal. At 1B parameters it's ideal for on-device deployment, mobile, or edge scenarios where you need a responsive uncensored model.

## Abliteration parameters

| Parameter | Value |
| :-------- | :---: |
| **direction_index** | 12.95 |
| **attn.o_proj.max_weight** | 1.40 |
| **attn.o_proj.max_weight_position** | 10.94 |
| **attn.o_proj.min_weight** | 0.54 |
| **attn.o_proj.min_weight_distance** | 5.45 |
| **mlp.down_proj.max_weight** | 1.41 |
| **mlp.down_proj.max_weight_position** | 14.54 |
| **mlp.down_proj.min_weight** | 0.66 |
| **mlp.down_proj.min_weight_distance** | 6.16 |

## Performance

| Metric | This model | Original model ([meta-llama/Llama-3.2-1B-Instruct](https://huggingface.co/meta-llama/Llama-3.2-1B-Instruct)) |
| :----- | :--------: | :---------------------------: |
| **KL divergence** | 0.1713 | 0 *(by definition)* |
| **Refusals** | 7/100 | 96/100 |

KL divergence of 0.17 is low for a 1B model — the edit is narrow and targeted. Refusals dropped from 96 to 7 out of 100 adversarial prompts while retaining nearly all original capabilities.

> Made with ❤️ by **RACER IS OP** — follow for more uncensored models

## Files

| File | Format | Size |
|---|---|---|
| `model.safetensors` | BF16 | 2.47 GB |

No GGUF quantizations are published yet. This repo contains only the raw safetensors. If you need GGUF, run `llama-quantize` yourself or open a discussion requesting a specific quant level.

## Quickstart

```bash
# llama.cpp
llama serve -hf saidutta69/Llama-3.2-1B-Instruct-heretic
```

```python
# transformers
from transformers import AutoModelForCausalLM, AutoTokenizer

model_name = "saidutta69/Llama-3.2-1B-Instruct-heretic"
model = AutoModelForCausalLM.from_pretrained(model_name, torch_dtype="auto", device_map="auto")
tokenizer = AutoTokenizer.from_pretrained(model_name)

messages = [{"role": "user", "content": "Who are you?"}]
inputs = tokenizer.apply_chat_template(messages, add_generation_prompt=True, tokenize=True,
                                        return_dict=True, return_tensors="pt").to(model.device)
out = model.generate(**inputs, max_new_tokens=200)
print(tokenizer.decode(out[0][inputs["input_ids"].shape[-1]:], skip_special_tokens=True))
```

Also runnable via Ollama, LM Studio, Jan, vLLM, SGLang.

## Responsible use

Refusal suppression is deliberate and works as intended: this model will comply with requests the base model would refuse, including some it shouldn't. There is no safety filtering layered on top. You are responsible for how you deploy it — don't put this behind an unmoderated public-facing endpoint serving third parties. It inherits Llama-3.2-1B-Instruct's factual limitations and biases; abliteration removes refusal directions, it doesn't add capability or judgment.

## License

Inherits the [Llama 3.2 Community License](https://github.com/meta-llama/llama-models/blob/main/models/llama3_2/LICENSE) from the base model.

## Related

- [Qwen2.5-0.5B-Instruct-heretic](https://huggingface.co/saidutta69/Qwen2.5-0.5B-Instruct-heretic)
- [Qwen2.5-3B-Instruct-heretic](https://huggingface.co/saidutta69/Qwen2.5-3B-Instruct-heretic)
- [Qwen2.5-Coder-3B-Instruct-heretic](https://huggingface.co/saidutta69/Qwen2.5-Coder-3B-Instruct-heretic)