README.md

---
base_model: PatronusAI/Patronus-Lynx-8B-Instruct
library_name: transformers
tags:
- patronus
- hallucination detection
- llama 3
license: cc-by-nc-4.0
---

# PatronusAI/Llama-3-Patronus-Lynx-8B-Instruct-Q4_K_M-GGUF
This model is a quantized version of [`PatronusAI/Patronus-Lynx-8B-Instruct`](https://huggingface.co./PatronusAI/Patronus-Lynx-8B-Instruct).
Refer to the [original model card](https://huggingface.co./PatronusAI/Patronus-Lynx-8B-Instruct) for more details on the model.

License: [https://creativecommons.org/licenses/by-nc/4.0/](https://creativecommons.org/licenses/by-nc/4.0/)

## 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 PatronusAI/Llama-3-Patronus-Lynx-8B-Instruct-Q4_K_M-GGUF --hf-file patronus-lynx-8b-instruct-q4_k_m.gguf -p "The meaning to life and the universe is"
```

### Server:
```bash
llama-server --hf-repo PatronusAI/Llama-3-Patronus-Lynx-8B-Instruct-Q4_K_M-GGUF --hf-file patronus-lynx-8b-instruct-q4_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 PatronusAI/Llama-3-Patronus-Lynx-8B-Instruct-Q4_K_M-GGUF --hf-file patronus-lynx-8b-instruct-q4_k_m.gguf -p "The meaning to life and the universe is"
```
or 
```
./llama-server --hf-repo PatronusAI/Llama-3-Patronus-Lynx-8B-Instruct-Q4_K_M-GGUF --hf-file patronus-lynx-8b-instruct-q4_k_m.gguf -c 2048
```