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

Use Docker

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

Llama new
LM Studio
Jan

vLLM

How to use QuantFactory/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 "QuantFactory/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": "QuantFactory/Meta-Llama-3-8B-Instruct-GGUF",
		"messages": [
			{
				"role": "user",
				"content": "What is the capital of France?"
			}
		]
	}'

Use Docker

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

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

Lemonade

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

Pull the model

# Download Lemonade from https://lemonade-server.ai/
lemonade pull QuantFactory/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

This quantized Llama3 cannot answer in different language like original Meta Llama3 model

#16

by taiSupermicro - opened May 20, 2024

Discussion

taiSupermicro

May 20, 2024

•

edited May 22, 2024

Llama 3 can answer in different languages while Llama2 will understand different language but still answer in English. It turned out that, this model card is still answering in English. So I wonder what happen after quantized the original model from Meta ?

taiSupermicro changed discussion title from Is this truly quantized Llama3 or Llama2 ? to This quantized Llama3 cannot answer in different language liek original Meta Llama3 model May 20, 2024

taiSupermicro changed discussion title from This quantized Llama3 cannot answer in different language liek original Meta Llama3 model to This quantized Llama3 cannot answer in different language like original Meta Llama3 model May 20, 2024

taiSupermicro changed discussion status to closed May 22, 2024

taiSupermicro changed discussion status to open May 22, 2024

munish0838

Quant Factory org May 23, 2024

Can you try if this works https://huggingface.co/QuantFactory/Meta-Llama-3-8B-Instruct-GGUF-v2

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