Frigg V2 8b ACADEMIC 128K Q4 K M GGUF

🚀 Frigg-v2-8b-ACADEMIC-128K-Q4_K_M-GGUF

This project provides a model in GGUF format, which is converted from the original MrRobotoAI/Frigg-v2-8b-ACADEMIC-128K. It supports various text - related tasks such as text generation, translation, and summarization.

✨ Features

• Multiple Task Support: Capable of text generation, text - to - text generation, translation, summarization, and document question - answering.
• GGUF Format: Converted to the efficient GGUF format using llama.cpp via ggml.ai's GGUF - my - repo space.

📦 Installation

Install llama.cpp via Brew

You can install llama.cpp through brew (works on Mac and Linux):

brew install llama.cpp

💻 Usage Examples

Basic Usage

CLI

llama-cli --hf-repo MrRobotoAI/Frigg-v2-8b-ACADEMIC-128K-Q4_K_M-GGUF --hf-file frigg-v2-8b-academic-128k-q4_k_m.gguf -p "The meaning to life and the universe is"

Server

llama-server --hf-repo MrRobotoAI/Frigg-v2-8b-ACADEMIC-128K-Q4_K_M-GGUF --hf-file frigg-v2-8b-academic-128k-q4_k_m.gguf -c 2048

Advanced Usage

If you want to use this checkpoint directly through the steps in the Llama.cpp repo:

Step 1: Clone llama.cpp from GitHub

git clone https://github.com/ggerganov/llama.cpp

Step 2: Build llama.cpp 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

./llama-cli --hf-repo MrRobotoAI/Frigg-v2-8b-ACADEMIC-128K-Q4_K_M-GGUF --hf-file frigg-v2-8b-academic-128k-q4_k_m.gguf -p "The meaning to life and the universe is"

or

./llama-server --hf-repo MrRobotoAI/Frigg-v2-8b-ACADEMIC-128K-Q4_K_M-GGUF --hf-file frigg-v2-8b-academic-128k-q4_k_m.gguf -c 2048

📚 Documentation

Refer to the original model card for more details on the model.

📄 Information Table