---
base_model:
- mlabonne/Hermes-3-Llama-3.1-8B-lorablated
library_name: transformers
tags:
- mergekit
- merge
- autoquant
- gguf
---

# 🪽 Hermes-3-Llama-3.1-8B-lorablated

![image/png](https://cdn-uploads.huggingface.co/production/uploads/61b8e2ba285851687028d395/4Hbw5n68jKUSBQeTqQIeT.png)

This is an uncensored version of [NousResearch/Hermes-3-Llama-3.1-8B](https://huggingface.co/NousResearch/Hermes-3-Llama-3.1-8B) using lorablation.

You can see in the following example how Hermes 3 refuses to answer a legitimate question while the abliterated model complies:

![image/png](https://cdn-uploads.huggingface.co/production/uploads/61b8e2ba285851687028d395/GM0WXDXmUU1dRJdYi-Py0.png)

The recipe is simple:

1. **Extraction**: We extract a LoRA adapter by comparing two models: a censored Llama 3.1 ([meta-llama/Meta-Llama-3-8B-Instruct](https://huggingface.co/meta-llama/Meta-Llama-3-8B-Instruct)) and an abliterated Llama 3.1 ([mlabonne/Meta-Llama-3.1-8B-Instruct-abliterated](https://huggingface.co/mlabonne/Meta-Llama-3.1-8B-Instruct-abliterated)).
2. **Merge**: We merge this new LoRA adapter using [task arithmetic](https://arxiv.org/abs/2212.04089) to the censored [NousResearch/Hermes-3-Llama-3.1-8B](https://huggingface.co/NousResearch/Hermes-3-Llama-3.1-8B) to abliterate it.

See [this article](https://huggingface.co/blog/mlabonne/abliteration) to learn more about abliteration.

## 🧩 Configuration

This model was merged using the [task arithmetic](https://arxiv.org/abs/2212.04089) merge method using [NousResearch/Hermes-3-Llama-3.1-8B](https://huggingface.co/NousResearch/Hermes-3-Llama-3.1-8B) + Llama-3.1-8B-Instruct-abliterated-LORA as a base.

The following YAML configuration was used to produce this model:

```yaml
base_model: NousResearch/Hermes-3-Llama-3.1-8B+Llama-3.1-8B-Instruct-abliterated-LORA
dtype: bfloat16
merge_method: task_arithmetic
parameters:
  normalize: false
slices:
- sources:
  - layer_range: [0, 32]
    model: NousResearch/Hermes-3-Llama-3.1-8B+Llama-3.1-8B-Instruct-abliterated-LORA
    parameters:
      weight: 1.0
```