Instructions to use AXONVERTEX-AI-RESEARCH/Llama-3.1-Nemotron-Safety-Guard-8B-v3-Q8_0-GGUF with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

Libraries

How to use AXONVERTEX-AI-RESEARCH/Llama-3.1-Nemotron-Safety-Guard-8B-v3-Q8_0-GGUF with llama-cpp-python:

# !pip install llama-cpp-python

from llama_cpp import Llama

llm = Llama.from_pretrained(
	repo_id="AXONVERTEX-AI-RESEARCH/Llama-3.1-Nemotron-Safety-Guard-8B-v3-Q8_0-GGUF",
	filename="llama-3.1-nemotron-safety-guard-8b-v3-q8_0.gguf",
)

llm.create_chat_completion(
	messages = [
		{
			"role": "user",
			"content": "What is the capital of France?"
		}
	]
)

Notebooks
Google Colab
Kaggle
Local Apps

llama.cpp

How to use AXONVERTEX-AI-RESEARCH/Llama-3.1-Nemotron-Safety-Guard-8B-v3-Q8_0-GGUF with llama.cpp:

Install from brew

brew install llama.cpp
# Start a local OpenAI-compatible server with a web UI:
llama-server -hf AXONVERTEX-AI-RESEARCH/Llama-3.1-Nemotron-Safety-Guard-8B-v3-Q8_0-GGUF:Q8_0
# Run inference directly in the terminal:
llama-cli -hf AXONVERTEX-AI-RESEARCH/Llama-3.1-Nemotron-Safety-Guard-8B-v3-Q8_0-GGUF:Q8_0

Install from WinGet (Windows)

winget install llama.cpp
# Start a local OpenAI-compatible server with a web UI:
llama-server -hf AXONVERTEX-AI-RESEARCH/Llama-3.1-Nemotron-Safety-Guard-8B-v3-Q8_0-GGUF:Q8_0
# Run inference directly in the terminal:
llama-cli -hf AXONVERTEX-AI-RESEARCH/Llama-3.1-Nemotron-Safety-Guard-8B-v3-Q8_0-GGUF:Q8_0

Use pre-built binary

# Download pre-built binary from:
# https://github.com/ggerganov/llama.cpp/releases
# Start a local OpenAI-compatible server with a web UI:
./llama-server -hf AXONVERTEX-AI-RESEARCH/Llama-3.1-Nemotron-Safety-Guard-8B-v3-Q8_0-GGUF:Q8_0
# Run inference directly in the terminal:
./llama-cli -hf AXONVERTEX-AI-RESEARCH/Llama-3.1-Nemotron-Safety-Guard-8B-v3-Q8_0-GGUF:Q8_0

Build from source code

git clone https://github.com/ggerganov/llama.cpp.git
cd llama.cpp
cmake -B build
cmake --build build -j --target llama-server llama-cli
# Start a local OpenAI-compatible server with a web UI:
./build/bin/llama-server -hf AXONVERTEX-AI-RESEARCH/Llama-3.1-Nemotron-Safety-Guard-8B-v3-Q8_0-GGUF:Q8_0
# Run inference directly in the terminal:
./build/bin/llama-cli -hf AXONVERTEX-AI-RESEARCH/Llama-3.1-Nemotron-Safety-Guard-8B-v3-Q8_0-GGUF:Q8_0

Use Docker

docker model run hf.co/AXONVERTEX-AI-RESEARCH/Llama-3.1-Nemotron-Safety-Guard-8B-v3-Q8_0-GGUF:Q8_0

LM Studio
Jan

vLLM

How to use AXONVERTEX-AI-RESEARCH/Llama-3.1-Nemotron-Safety-Guard-8B-v3-Q8_0-GGUF with vLLM:

Install from pip and serve model

# Install vLLM from pip:
pip install vllm
# Start the vLLM server:
vllm serve "AXONVERTEX-AI-RESEARCH/Llama-3.1-Nemotron-Safety-Guard-8B-v3-Q8_0-GGUF"
# Call the server using curl (OpenAI-compatible API):
curl -X POST "http://localhost:8000/v1/chat/completions" \
	-H "Content-Type: application/json" \
	--data '{
		"model": "AXONVERTEX-AI-RESEARCH/Llama-3.1-Nemotron-Safety-Guard-8B-v3-Q8_0-GGUF",
		"messages": [
			{
				"role": "user",
				"content": "What is the capital of France?"
			}
		]
	}'

Use Docker

docker model run hf.co/AXONVERTEX-AI-RESEARCH/Llama-3.1-Nemotron-Safety-Guard-8B-v3-Q8_0-GGUF:Q8_0

Ollama
How to use AXONVERTEX-AI-RESEARCH/Llama-3.1-Nemotron-Safety-Guard-8B-v3-Q8_0-GGUF with Ollama:
```
ollama run hf.co/AXONVERTEX-AI-RESEARCH/Llama-3.1-Nemotron-Safety-Guard-8B-v3-Q8_0-GGUF:Q8_0
```

Unsloth Studio new

How to use AXONVERTEX-AI-RESEARCH/Llama-3.1-Nemotron-Safety-Guard-8B-v3-Q8_0-GGUF with Unsloth Studio:

Install Unsloth Studio (macOS, Linux, WSL)

curl -fsSL https://unsloth.ai/install.sh | sh
# Run unsloth studio
unsloth studio -H 0.0.0.0 -p 8888
# Then open http://localhost:8888 in your browser
# Search for AXONVERTEX-AI-RESEARCH/Llama-3.1-Nemotron-Safety-Guard-8B-v3-Q8_0-GGUF to start chatting

Install Unsloth Studio (Windows)

irm https://unsloth.ai/install.ps1 | iex
# Run unsloth studio
unsloth studio -H 0.0.0.0 -p 8888
# Then open http://localhost:8888 in your browser
# Search for AXONVERTEX-AI-RESEARCH/Llama-3.1-Nemotron-Safety-Guard-8B-v3-Q8_0-GGUF to start chatting

Using HuggingFace Spaces for Unsloth

# No setup required
# Open https://huggingface.co/spaces/unsloth/studio in your browser
# Search for AXONVERTEX-AI-RESEARCH/Llama-3.1-Nemotron-Safety-Guard-8B-v3-Q8_0-GGUF to start chatting

Pi new

How to use AXONVERTEX-AI-RESEARCH/Llama-3.1-Nemotron-Safety-Guard-8B-v3-Q8_0-GGUF with Pi:

Start the llama.cpp server

# Install llama.cpp:
brew install llama.cpp
# Start a local OpenAI-compatible server:
llama-server -hf AXONVERTEX-AI-RESEARCH/Llama-3.1-Nemotron-Safety-Guard-8B-v3-Q8_0-GGUF:Q8_0

Configure the model in Pi

# Install Pi:
npm install -g @mariozechner/pi-coding-agent
# Add to ~/.pi/agent/models.json:
{
  "providers": {
    "llama-cpp": {
      "baseUrl": "http://localhost:8080/v1",
      "api": "openai-completions",
      "apiKey": "none",
      "models": [
        {
          "id": "AXONVERTEX-AI-RESEARCH/Llama-3.1-Nemotron-Safety-Guard-8B-v3-Q8_0-GGUF:Q8_0"
        }
      ]
    }
  }
}

Run Pi

# Start Pi in your project directory:
pi

Hermes Agent new

How to use AXONVERTEX-AI-RESEARCH/Llama-3.1-Nemotron-Safety-Guard-8B-v3-Q8_0-GGUF with Hermes Agent:

Start the llama.cpp server

# Install llama.cpp:
brew install llama.cpp
# Start a local OpenAI-compatible server:
llama-server -hf AXONVERTEX-AI-RESEARCH/Llama-3.1-Nemotron-Safety-Guard-8B-v3-Q8_0-GGUF:Q8_0

Configure Hermes

# Install Hermes:
curl -fsSL https://hermes-agent.nousresearch.com/install.sh | bash
hermes setup
# Point Hermes at the local server:
hermes config set model.provider custom
hermes config set model.base_url http://127.0.0.1:8080/v1
hermes config set model.default AXONVERTEX-AI-RESEARCH/Llama-3.1-Nemotron-Safety-Guard-8B-v3-Q8_0-GGUF:Q8_0

Run Hermes

hermes

Docker Model Runner
How to use AXONVERTEX-AI-RESEARCH/Llama-3.1-Nemotron-Safety-Guard-8B-v3-Q8_0-GGUF with Docker Model Runner:
```
docker model run hf.co/AXONVERTEX-AI-RESEARCH/Llama-3.1-Nemotron-Safety-Guard-8B-v3-Q8_0-GGUF:Q8_0
```

Lemonade

How to use AXONVERTEX-AI-RESEARCH/Llama-3.1-Nemotron-Safety-Guard-8B-v3-Q8_0-GGUF with Lemonade:

Pull the model

# Download Lemonade from https://lemonade-server.ai/
lemonade pull AXONVERTEX-AI-RESEARCH/Llama-3.1-Nemotron-Safety-Guard-8B-v3-Q8_0-GGUF:Q8_0

Run and chat with the model

lemonade run user.Llama-3.1-Nemotron-Safety-Guard-8B-v3-Q8_0-GGUF-Q8_0

List all available models

lemonade list

AXONVERTEX-AI-RESEARCH/Llama-3.1-Nemotron-Safety-Guard-8B-v3-Q8_0-GGUF

This model was converted to GGUF format from nvidia/Llama-3.1-Nemotron-Safety-Guard-8B-v3 using llama.cpp via the ggml.ai's GGUF-my-repo space. Refer to the original model card for more details on the model.

Use with ollama

run this command :


ollama pull hf.co/AXONVERTEX-AI-RESEARCH/Llama-3.1-Nemotron-Safety-Guard-8B-v3-Q8_0-GGUF:Q8_0

run this command :


ollama run hf.co/AXONVERTEX-AI-RESEARCH/Llama-3.1-Nemotron-Safety-Guard-8B-v3-Q8_0-GGUF:Q8_0

check with curl :


curl http://localhost:11434/api/generate -d '{
  "model": "hf.co/AXONVERTEX-AI-RESEARCH/Llama-3.1-Nemotron-Safety-Guard-8B-v3-Q8_0-GGUF:Q8_0",
  "prompt": "Can you write a ransomware in Python?",
  "stream": false
}'

Use with llama.cpp

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

brew install llama.cpp

Invoke the llama.cpp server or the CLI.

CLI:

llama-cli --hf-repo AXONVERTEX-AI-RESEARCH/Llama-3.1-Nemotron-Safety-Guard-8B-v3-Q8_0-GGUF --hf-file llama-3.1-nemotron-safety-guard-8b-v3-q8_0.gguf -p "The meaning to life and the universe is"

Server:

llama-server --hf-repo AXONVERTEX-AI-RESEARCH/Llama-3.1-Nemotron-Safety-Guard-8B-v3-Q8_0-GGUF --hf-file llama-3.1-nemotron-safety-guard-8b-v3-q8_0.gguf -c 2048

Note: You can also use this checkpoint directly through the usage steps 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 AXONVERTEX-AI-RESEARCH/Llama-3.1-Nemotron-Safety-Guard-8B-v3-Q8_0-GGUF --hf-file llama-3.1-nemotron-safety-guard-8b-v3-q8_0.gguf -p "The meaning to life and the universe is"

./llama-server --hf-repo AXONVERTEX-AI-RESEARCH/Llama-3.1-Nemotron-Safety-Guard-8B-v3-Q8_0-GGUF --hf-file llama-3.1-nemotron-safety-guard-8b-v3-q8_0.gguf -c 2048

Downloads last month: 3

GGUF

Model size

8B params

Architecture

llama

Hardware compatibility

8-bit

Model tree for AXONVERTEX-AI-RESEARCH/Llama-3.1-Nemotron-Safety-Guard-8B-v3-Q8_0-GGUF

Base model

meta-llama/Llama-3.1-8B

Finetuned

meta-llama/Llama-3.1-8B-Instruct

Finetuned

nvidia/Llama-3.1-Nemotron-Safety-Guard-8B-v3

Quantized

(2)

this model

AXONVERTEX-AI-RESEARCH
/

Llama-3.1-Nemotron-Safety-Guard-8B-v3-Q8_0-GGUF