README.md

---
library_name: transformers
tags:
- roleplay
- rp
- human
- llama-cpp
- gguf-my-repo
license: apache-2.0
datasets:
- ResplendentAI/NSFW_RP_Format_DPO
- Undi95/Weyaxi-humanish-dpo-project-noemoji
base_model: vicgalle/Roleplay-Hermes-3-Llama-3.1-8B
---

# Triangle104/Roleplay-Hermes-3-Llama-3.1-8B-Q5_K_M-GGUF
This model was converted to GGUF format from [`vicgalle/Roleplay-Hermes-3-Llama-3.1-8B`](https://huggingface.co/vicgalle/Roleplay-Hermes-3-Llama-3.1-8B) 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/vicgalle/Roleplay-Hermes-3-Llama-3.1-8B) for more details on the model.

---
Model details:
-
A DPO-tuned Hermes-3-Llama-3.1-8B to behave more "humanish", i.e., 
avoiding AI assistant slop. It also works for role-play (RP). To achieve
 this, the model was fine-tuned over a series of datasets:


Undi95/Weyaxi-humanish-dpo-project-noemoji, to make the model react as a human, rejecting assistant-like or too neutral responses.
ResplendentAI/NSFW_RP_Format_DPO, to steer the model 
towards using the *action* format in RP settings. Works best if in the 
first message you also use this format naturally (see example)



	
		
	

		Usage example
	



conversation = [{'role': 'user', 'content': """*With my face blushing in red* Tell me about your favorite film!"""}]

prompt = tokenizer.apply_chat_template(conversation, tokenize=False, add_generation_prompt=True)

inputs = tokenizer(prompt, return_tensors="pt").to(model.device) 

outputs = model.generate(**inputs, max_new_tokens=512, do_sample=True, temperature=0.8)



The response is




*blushing* Aw, that's a tough one! There are so many great films out 
there. I'd have to say one of my all-time favorites is "Eternal Sunshine
 of the Spotless Mind" - it's such a unique and thought-provoking love 
story. But really, there are so many amazing films! What's your 
favorite? *I hope mine is at least somewhat decent!*




Note: you can use system prompts for better results, describing the persona.

---
## 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/Roleplay-Hermes-3-Llama-3.1-8B-Q5_K_M-GGUF --hf-file roleplay-hermes-3-llama-3.1-8b-q5_k_m.gguf -p "The meaning to life and the universe is"
```

### Server:
```bash
llama-server --hf-repo Triangle104/Roleplay-Hermes-3-Llama-3.1-8B-Q5_K_M-GGUF --hf-file roleplay-hermes-3-llama-3.1-8b-q5_k_m.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/Roleplay-Hermes-3-Llama-3.1-8B-Q5_K_M-GGUF --hf-file roleplay-hermes-3-llama-3.1-8b-q5_k_m.gguf -p "The meaning to life and the universe is"
```
or 
```
./llama-server --hf-repo Triangle104/Roleplay-Hermes-3-Llama-3.1-8B-Q5_K_M-GGUF --hf-file roleplay-hermes-3-llama-3.1-8b-q5_k_m.gguf -c 2048
```