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

Libraries

How to use starble-dev/Meta-Llama-3.1-8B-Instruct-GGUF with Transformers:

# Load model directly
from transformers import AutoModel
model = AutoModel.from_pretrained("starble-dev/Meta-Llama-3.1-8B-Instruct-GGUF", device_map="auto")

Notebooks
Google Colab
Kaggle
Local Apps Settings

llama.cpp

How to use starble-dev/Meta-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 starble-dev/Meta-Llama-3.1-8B-Instruct-GGUF:Q4_K_M
# Run inference directly in the terminal:
llama cli -hf starble-dev/Meta-Llama-3.1-8B-Instruct-GGUF:Q4_K_M

Install from WinGet (Windows)

winget install llama.cpp
# Start a local OpenAI-compatible server with a web UI:
llama serve -hf starble-dev/Meta-Llama-3.1-8B-Instruct-GGUF:Q4_K_M
# Run inference directly in the terminal:
llama cli -hf starble-dev/Meta-Llama-3.1-8B-Instruct-GGUF:Q4_K_M

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 starble-dev/Meta-Llama-3.1-8B-Instruct-GGUF:Q4_K_M
# Run inference directly in the terminal:
./llama-cli -hf starble-dev/Meta-Llama-3.1-8B-Instruct-GGUF:Q4_K_M

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 starble-dev/Meta-Llama-3.1-8B-Instruct-GGUF:Q4_K_M
# Run inference directly in the terminal:
./build/bin/llama-cli -hf starble-dev/Meta-Llama-3.1-8B-Instruct-GGUF:Q4_K_M

Use Docker

docker model run hf.co/starble-dev/Meta-Llama-3.1-8B-Instruct-GGUF:Q4_K_M

LM Studio
Jan
Ollama
How to use starble-dev/Meta-Llama-3.1-8B-Instruct-GGUF with Ollama:
```
ollama run hf.co/starble-dev/Meta-Llama-3.1-8B-Instruct-GGUF:Q4_K_M
```

Unsloth Studio

How to use starble-dev/Meta-Llama-3.1-8B-Instruct-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 starble-dev/Meta-Llama-3.1-8B-Instruct-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 starble-dev/Meta-Llama-3.1-8B-Instruct-GGUF to start chatting

Using HuggingFace Spaces for Unsloth

# No setup required
# Open https://huggingface.co/spaces/unsloth/studio in your browser
# Search for starble-dev/Meta-Llama-3.1-8B-Instruct-GGUF to start chatting

Docker Model Runner
How to use starble-dev/Meta-Llama-3.1-8B-Instruct-GGUF with Docker Model Runner:
```
docker model run hf.co/starble-dev/Meta-Llama-3.1-8B-Instruct-GGUF:Q4_K_M
```

Lemonade

How to use starble-dev/Meta-Llama-3.1-8B-Instruct-GGUF with Lemonade:

Pull the model

# Download Lemonade from https://lemonade-server.ai/
lemonade pull starble-dev/Meta-Llama-3.1-8B-Instruct-GGUF:Q4_K_M

Run and chat with the model

lemonade run user.Meta-Llama-3.1-8B-Instruct-GGUF-Q4_K_M

List all available models

lemonade list

Atomic Chat

NOTICE:
Llama-3.1 is licensed under Llama 3.1 Community License
A copy of this license is available at this repo, here

Original Model: meta-llama/Meta-Llama-3.1-8B-Instruct

How to Use: llama.cpp

Original Model License: Llama 3.1 Community License

Release Used: b3441

Quants

Name	Quant Type	Size
Meta-Llama-3.1-8B-Instruct-Q2_K.gguf	Q2_K	3.18 GB
Meta-Llama-3.1-8B-Instruct-Q3_K_S.gguf	Q3_K_S	3.66 GB
Meta-Llama-3.1-8B-Instruct-Q3_K_M.gguf	Q3_K_M	4.02 GB
Meta-Llama-3.1-8B-Instruct-Q3_K_L.gguf	Q3_K_L	4.32 GB
Meta-Llama-3.1-8B-Instruct-Q4_K_S.gguf	Q4_K_S	4.69 GB
Meta-Llama-3.1-8B-Instruct-Q4_K_M.gguf	Q4_K_M	4.92 GB
Meta-Llama-3.1-8B-Instruct-Q5_K_S.gguf	Q5_K_S	5.60 GB
Meta-Llama-3.1-8B-Instruct-Q5_K_M.gguf	Q5_K_M	5.73 GB
Meta-Llama-3.1-8B-Instruct-Q6_K.gguf	Q6_K	6.60 GB
Meta-Llama-3.1-8B-Instruct-Q8_0.gguf	Q8_0	8.54 GB

Downloads last month: 383

GGUF

Model size

8B params

Architecture

llama

Hardware compatibility

2-bit

3-bit

4-bit

5-bit

6-bit

8-bit

Inference Providers NEW

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Model tree for starble-dev/Meta-Llama-3.1-8B-Instruct-GGUF

Base model

meta-llama/Llama-3.1-8B

Finetuned

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

Quantized

(893)

this model