Instructions to use bartowski/Meta-Llama-3-8B-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 bartowski/Meta-Llama-3-8B-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 bartowski/Meta-Llama-3-8B-Instruct-GGUF:Q4_K_M
# Run inference directly in the terminal:
llama cli -hf bartowski/Meta-Llama-3-8B-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 bartowski/Meta-Llama-3-8B-Instruct-GGUF:Q4_K_M
# Run inference directly in the terminal:
llama cli -hf bartowski/Meta-Llama-3-8B-Instruct-GGUF:Q4_K_M

Build from source code

git clone https://github.com/ggml-org/llama.cpp.git
cd llama.cpp
cmake -B build
cmake --build build -j --target llama-app
# Start a local OpenAI-compatible server with a web UI:
./build/bin/llama serve -hf bartowski/Meta-Llama-3-8B-Instruct-GGUF:Q4_K_M
# Run inference directly in the terminal:
./build/bin/llama cli -hf bartowski/Meta-Llama-3-8B-Instruct-GGUF:Q4_K_M

Use Docker

docker model run hf.co/bartowski/Meta-Llama-3-8B-Instruct-GGUF:Q4_K_M

Llama new
LM Studio
Jan

vLLM

How to use bartowski/Meta-Llama-3-8B-Instruct-GGUF with vLLM:

Install from pip and serve model

# Install vLLM from pip:
pip install vllm
# Start the vLLM server:
vllm serve "bartowski/Meta-Llama-3-8B-Instruct-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": "bartowski/Meta-Llama-3-8B-Instruct-GGUF",
		"messages": [
			{
				"role": "user",
				"content": "What is the capital of France?"
			}
		]
	}'

Use Docker

docker model run hf.co/bartowski/Meta-Llama-3-8B-Instruct-GGUF:Q4_K_M

Ollama
How to use bartowski/Meta-Llama-3-8B-Instruct-GGUF with Ollama:
```
ollama run hf.co/bartowski/Meta-Llama-3-8B-Instruct-GGUF:Q4_K_M
```
Unsloth Desktop
Docker Model Runner
How to use bartowski/Meta-Llama-3-8B-Instruct-GGUF with Docker Model Runner:
```
docker model run hf.co/bartowski/Meta-Llama-3-8B-Instruct-GGUF:Q4_K_M
```

Lemonade

How to use bartowski/Meta-Llama-3-8B-Instruct-GGUF with Lemonade:

Pull the model

# Download Lemonade from https://lemonade-server.ai/
lemonade pull bartowski/Meta-Llama-3-8B-Instruct-GGUF:Q4_K_M

Run and chat with the model

lemonade run user.Meta-Llama-3-8B-Instruct-GGUF-Q4_K_M

List all available models

lemonade list

Atomic Chat

New discussion

Resources

View closed (3)

Update metadata (general.name)

#12 opened 10 months ago by

riki-1103

yes

#11 opened about 1 year ago by

5k-taken

Something is up with the download, its not right.

#10 opened over 1 year ago by

BigShadex

Bug in tokenize()/detokenize()/tokenize() cycle

#9 opened over 2 years ago by

riedgar-ms

Llama 3 8B Instruct - Q8 vs FP16 vs FP32

#8 opened over 2 years ago by

Hearcharted

Can you make CodeQwen1.5-7B-Chat IQ4_XS version?

#6 opened over 2 years ago by

Dotoro22

Anyone experiences quality degrade for math question?

#4 opened over 2 years ago by

tankstarwar

You think you could re-quant with the regex fix?

#3 opened over 2 years ago by

YearZero

Hi - are you going add new llama 70b version as well?

#1 opened over 2 years ago by

mirek190