Instructions to use beyond-logic-labs/Llama-3.1-8B-Instruct-GGUF with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

Notebooks
Google Colab
Kaggle
Local Apps Settings

How to use beyond-logic-labs/Llama-3.1-8B-Instruct-GGUF with llama.cpp:

Install (macOS, Linux)

curl -LsSf https://llama.app/install.sh | sh
# Start a local OpenAI-compatible server with a web UI:
llama serve -hf beyond-logic-labs/Llama-3.1-8B-Instruct-GGUF:Q6_K
# Run inference directly in the terminal:
llama cli -hf beyond-logic-labs/Llama-3.1-8B-Instruct-GGUF:Q6_K

Install from WinGet (Windows)

winget install llama.cpp
# Start a local OpenAI-compatible server with a web UI:
llama serve -hf beyond-logic-labs/Llama-3.1-8B-Instruct-GGUF:Q6_K
# Run inference directly in the terminal:
llama cli -hf beyond-logic-labs/Llama-3.1-8B-Instruct-GGUF:Q6_K

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 beyond-logic-labs/Llama-3.1-8B-Instruct-GGUF:Q6_K
# Run inference directly in the terminal:
./llama-cli -hf beyond-logic-labs/Llama-3.1-8B-Instruct-GGUF:Q6_K

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 beyond-logic-labs/Llama-3.1-8B-Instruct-GGUF:Q6_K
# Run inference directly in the terminal:
./build/bin/llama-cli -hf beyond-logic-labs/Llama-3.1-8B-Instruct-GGUF:Q6_K

Use Docker

docker model run hf.co/beyond-logic-labs/Llama-3.1-8B-Instruct-GGUF:Q6_K

LM Studio
Jan
Ollama
How to use beyond-logic-labs/Llama-3.1-8B-Instruct-GGUF with Ollama:
```
ollama run hf.co/beyond-logic-labs/Llama-3.1-8B-Instruct-GGUF:Q6_K
```
Unsloth Desktop

How to use beyond-logic-labs/Llama-3.1-8B-Instruct-GGUF with Pi:

Start the llama.cpp server

# Install llama.cpp:
brew install llama.cpp
# Start a local OpenAI-compatible server:
llama serve -hf beyond-logic-labs/Llama-3.1-8B-Instruct-GGUF:Q6_K

Configure the model in Pi

# Install Pi:
npm install -g @earendil-works/pi-coding-agent
# Add to ~/.pi/agent/models.json:
{
  "providers": {
    "llama-cpp": {
      "baseUrl": "http://localhost:8080/v1",
      "api": "openai-completions",
      "apiKey": "none",
      "models": [
        {
          "id": "beyond-logic-labs/Llama-3.1-8B-Instruct-GGUF:Q6_K"
        }
      ]
    }
  }
}

Run Pi

# Start Pi in your project directory:
pi

Docker Model Runner
How to use beyond-logic-labs/Llama-3.1-8B-Instruct-GGUF with Docker Model Runner:
```
docker model run hf.co/beyond-logic-labs/Llama-3.1-8B-Instruct-GGUF:Q6_K
```

Lemonade

How to use beyond-logic-labs/Llama-3.1-8B-Instruct-GGUF with Lemonade:

Pull the model

# Download Lemonade from https://lemonade-server.ai/
lemonade pull beyond-logic-labs/Llama-3.1-8B-Instruct-GGUF:Q6_K

Run and chat with the model

lemonade run user.Llama-3.1-8B-Instruct-GGUF-Q6_K

List all available models

lemonade list

Hermes Agent

How to use beyond-logic-labs/Llama-3.1-8B-Instruct-GGUF with Hermes Agent:

Start the llama.cpp server

# Install llama.cpp:
brew install llama.cpp
# Start a local OpenAI-compatible server:
llama serve -hf beyond-logic-labs/Llama-3.1-8B-Instruct-GGUF:Q6_K

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 beyond-logic-labs/Llama-3.1-8B-Instruct-GGUF:Q6_K

Run Hermes

hermes

Atomic Chat

OpenClaw

How to use beyond-logic-labs/Llama-3.1-8B-Instruct-GGUF with OpenClaw:

Start the llama.cpp server

# Install llama.cpp:
brew install llama.cpp
# Start a local OpenAI-compatible server:
llama serve -hf beyond-logic-labs/Llama-3.1-8B-Instruct-GGUF:Q6_K

Configure OpenClaw

# Install OpenClaw:
npm install -g openclaw@latest
# Register the local server and set it as the default model:
openclaw onboard --non-interactive --mode local \
  --auth-choice custom-api-key \
  --custom-base-url http://127.0.0.1:8080/v1 \
  --custom-model-id "beyond-logic-labs/Llama-3.1-8B-Instruct-GGUF:Q6_K" \
  --custom-provider-id llama-cpp \
  --custom-compatibility openai \
  --custom-text-input \
  --accept-risk \
  --skip-health

Run OpenClaw

openclaw agent --local --agent main --message "Hello from Hugging Face"

Llama 3.1 8B Instruct - GGUF

GGUF quantized version of Meta's Llama 3.1 8B Instruct for use with llama.cpp, Ollama, LM Studio, and other GGUF-compatible inference engines.

Available Quantizations

Filename	Quant	Size	Description
`Llama-3.1-8B-Instruct-Q6_K.gguf`	Q6_K	~6.8 GB	High quality, recommended for most use cases

Usage

Ollama

ollama run hf.co/beyond-logic-labs/Llama-3.1-8B-Instruct-GGUF:Q6_K

LM Studio

Download the GGUF file and load it directly in LM Studio.

llama.cpp

./llama-cli -m Llama-3.1-8B-Instruct-Q6_K.gguf -p "You are a helpful assistant." -cnv

Model Details

Base Model: meta-llama/Llama-3.1-8B-Instruct
Context Length: 128K tokens
License: Llama 3.1 Community License

About Beyond Logic Labs

We build AI-powered tools for tabletop RPG players and game masters. Check out our other models for specialized RPG assistance.

Downloads last month: 5

GGUF

Model size

8B params

Architecture

llama

Hardware compatibility

6-bit

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Model tree for beyond-logic-labs/Llama-3.1-8B-Instruct-GGUF

Base model

meta-llama/Llama-3.1-8B

Finetuned

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

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