--- 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. ## ⚡ 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 ```