---
base_model:
- NousResearch/Hermes-3-Llama-3.1-8B
library_name: transformers
tags:
- mergekit
- merge
---
# 🪽 Hermes-3-Llama-3.1-8B-lorablated
![image/png](https://cdn-uploads.huggingface.co/production/uploads/61b8e2ba285851687028d395/4Hbw5n68jKUSBQeTqQIeT.png)
70B version: mlabonne/Hermes-3-Llama-3.1-70B-lorablated
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/61b8e2ba285851687028d395/2-ZRBvlZxvIr_Ag_ynNkk.png)
The recipe is based on @grimjim's [grimjim/Llama-3.1-8B-Instruct-abliterated_via_adapter](https://huggingface.co/grimjim/Llama-3.1-8B-Instruct-abliterated_via_adapter) (special thanks):
1. **Extraction**: We extract a LoRA adapter by comparing two models: a censored Llama 3.1 ([meta-llama/Meta-Llama-3.1-8B-Instruct](https://huggingface.co/meta-llama/Meta-Llama-3.1-8B-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.
![image/png](https://cdn-uploads.huggingface.co/production/uploads/61b8e2ba285851687028d395/JdYyK-HLHbyBiHvg-Nvsn.png)
See [this article](https://huggingface.co/blog/mlabonne/abliteration) to learn more about abliteration.
## âš¡ Quantization
* **GGUF**: https://huggingface.co/mlabonne/Hermes-3-Llama-3.1-8B-lorablated-GGUF
## 🧩 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
```
You can reproduce this model using the following commands:
```bash
# Setup
git clone https://github.com/arcee-ai/mergekit.git
cd mergekit && pip install -e .
pip install bitsandbytes
# Extraction
mergekit-extract-lora mlabonne/Meta-Llama-3.1-8B-Instruct-abliterated meta-llama/Meta-Llama-3.1-8B-Instruct Llama-3.1-8B-Instruct-abliterated-LORA --rank=64
# Merge using previous config
mergekit-yaml config.yaml Hermes-3-Llama-3.1-8B-lorablated --allow-crimes --lora-merge-cache=./cache
```