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---
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_S-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_S-GGUF --hf-file roleplay-hermes-3-llama-3.1-8b-q5_k_s.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_S-GGUF --hf-file roleplay-hermes-3-llama-3.1-8b-q5_k_s.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_S-GGUF --hf-file roleplay-hermes-3-llama-3.1-8b-q5_k_s.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_S-GGUF --hf-file roleplay-hermes-3-llama-3.1-8b-q5_k_s.gguf -c 2048
```
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