---
license: mit
base_model: nkpz/DeepHermes-3-Llama-3-8B-Preview-Uncensored-DeLMAT
tags:
- llama-cpp
- gguf-my-repo
---

# Triangle104/DeepHermes-3-Llama-3-8B-Preview-Uncensored-DeLMAT-Q8_0-GGUF
This model was converted to GGUF format from [`nkpz/DeepHermes-3-Llama-3-8B-Preview-Uncensored-DeLMAT`](https://huggingface.co/nkpz/DeepHermes-3-Llama-3-8B-Preview-Uncensored-DeLMAT) using llama.cpp via the ggml.ai's [GGUF-my-repo](https://huggingface.co/spaces/ggml-org/gguf-my-repo) space.
Refer to the [original model card](https://huggingface.co/nkpz/DeepHermes-3-Llama-3-8B-Preview-Uncensored-DeLMAT) for more details on the model.

---
 
   
    

	



				
				
				
				
				
					


					
					
					
					


						
							


							

	
This model is decensored using a technique I developed called DeLMAT:
 Decensoring Language Models through Activation Tuning. It's similar to 
the ablation / "abliteration" scripts that are out there, but works by 
training a LoRA adapter and calculating a loss based on the distance 
from the mean refusal activation and the distance between the mean 
acceptance activation.


The training script is released under the MIT license:
https://github.com/nkpz/DeLMAT


Rather than simply attempting to cancel out the refusal direction, 
DeLMAT guides the model toward an acceptance. In other words, instead of
 simply forgetting how to refuse requests, it learns to emphatically accept requests.

---

## Use with llama.cpp
Install llama.cpp through brew (works on Mac and Linux)

```bash
brew install llama.cpp

```
Invoke the llama.cpp server or the CLI.

### CLI:
```bash
llama-cli --hf-repo Triangle104/DeepHermes-3-Llama-3-8B-Preview-Uncensored-DeLMAT-Q8_0-GGUF --hf-file deephermes-3-llama-3-8b-preview-uncensored-delmat-q8_0.gguf -p "The meaning to life and the universe is"
```

### Server:
```bash
llama-server --hf-repo Triangle104/DeepHermes-3-Llama-3-8B-Preview-Uncensored-DeLMAT-Q8_0-GGUF --hf-file deephermes-3-llama-3-8b-preview-uncensored-delmat-q8_0.gguf -c 2048
```

Note: You can also use this checkpoint directly through the [usage steps](https://github.com/ggerganov/llama.cpp?tab=readme-ov-file#usage) listed in the Llama.cpp repo as well.

Step 1: Clone llama.cpp from GitHub.
```
git clone https://github.com/ggerganov/llama.cpp
```

Step 2: Move into the llama.cpp folder and build it with `LLAMA_CURL=1` flag along with other hardware-specific flags (for ex: LLAMA_CUDA=1 for Nvidia GPUs on Linux).
```
cd llama.cpp && LLAMA_CURL=1 make
```

Step 3: Run inference through the main binary.
```
./llama-cli --hf-repo Triangle104/DeepHermes-3-Llama-3-8B-Preview-Uncensored-DeLMAT-Q8_0-GGUF --hf-file deephermes-3-llama-3-8b-preview-uncensored-delmat-q8_0.gguf -p "The meaning to life and the universe is"
```
or 
```
./llama-server --hf-repo Triangle104/DeepHermes-3-Llama-3-8B-Preview-Uncensored-DeLMAT-Q8_0-GGUF --hf-file deephermes-3-llama-3-8b-preview-uncensored-delmat-q8_0.gguf -c 2048
```