Instructions to use LGAI-EXAONE/EXAONE-3.0-7.8B-Instruct with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

Libraries

How to use LGAI-EXAONE/EXAONE-3.0-7.8B-Instruct with Transformers:

# Use a pipeline as a high-level helper
from transformers import pipeline

pipe = pipeline("text-generation", model="LGAI-EXAONE/EXAONE-3.0-7.8B-Instruct", trust_remote_code=True)
messages = [
    {"role": "user", "content": "Who are you?"},
]
pipe(messages)

# Load model directly
from transformers import AutoModelForCausalLM
model = AutoModelForCausalLM.from_pretrained("LGAI-EXAONE/EXAONE-3.0-7.8B-Instruct", trust_remote_code=True, dtype="auto")

Notebooks
Google Colab
Kaggle
Local Apps Settings

vLLM

How to use LGAI-EXAONE/EXAONE-3.0-7.8B-Instruct with vLLM:

Install from pip and serve model

# Install vLLM from pip:
pip install vllm
# Start the vLLM server:
vllm serve "LGAI-EXAONE/EXAONE-3.0-7.8B-Instruct"
# Call the server using curl (OpenAI-compatible API):
curl -X POST "http://localhost:8000/v1/chat/completions" \
	-H "Content-Type: application/json" \
	--data '{
		"model": "LGAI-EXAONE/EXAONE-3.0-7.8B-Instruct",
		"messages": [
			{
				"role": "user",
				"content": "What is the capital of France?"
			}
		]
	}'

Use Docker

docker model run hf.co/LGAI-EXAONE/EXAONE-3.0-7.8B-Instruct

SGLang

How to use LGAI-EXAONE/EXAONE-3.0-7.8B-Instruct with SGLang:

Install from pip and serve model

# Install SGLang from pip:
pip install sglang
# Start the SGLang server:
python3 -m sglang.launch_server \
    --model-path "LGAI-EXAONE/EXAONE-3.0-7.8B-Instruct" \
    --host 0.0.0.0 \
    --port 30000
# Call the server using curl (OpenAI-compatible API):
curl -X POST "http://localhost:30000/v1/chat/completions" \
	-H "Content-Type: application/json" \
	--data '{
		"model": "LGAI-EXAONE/EXAONE-3.0-7.8B-Instruct",
		"messages": [
			{
				"role": "user",
				"content": "What is the capital of France?"
			}
		]
	}'

Use Docker images

docker run --gpus all \
    --shm-size 32g \
    -p 30000:30000 \
    -v ~/.cache/huggingface:/root/.cache/huggingface \
    --env "HF_TOKEN=<secret>" \
    --ipc=host \
    lmsysorg/sglang:latest \
    python3 -m sglang.launch_server \
        --model-path "LGAI-EXAONE/EXAONE-3.0-7.8B-Instruct" \
        --host 0.0.0.0 \
        --port 30000
# Call the server using curl (OpenAI-compatible API):
curl -X POST "http://localhost:30000/v1/chat/completions" \
	-H "Content-Type: application/json" \
	--data '{
		"model": "LGAI-EXAONE/EXAONE-3.0-7.8B-Instruct",
		"messages": [
			{
				"role": "user",
				"content": "What is the capital of France?"
			}
		]
	}'

Docker Model Runner
How to use LGAI-EXAONE/EXAONE-3.0-7.8B-Instruct with Docker Model Runner:
```
docker model run hf.co/LGAI-EXAONE/EXAONE-3.0-7.8B-Instruct
```

gguf quant please!!

by gopi87 - opened Aug 7, 2024

Discussion

gopi87

Aug 7, 2024

hi guys any gguf quant ?

jeonginkim

Aug 7, 2024

I'm curious. I hope someone uploads GGUF.

jeonginkim

Aug 7, 2024

I'm curious. I hope someone uploads GGUF.

It seems there's a no-sharing clause in this license. Unless LG releases it directly, it will be difficult to share.

mirek190

Aug 8, 2024

•

edited Aug 8, 2024

Just LOL

Most useless license I ever seen!
You even own output ?....lol x2
You can go to the forest with that sh** and burry .
Lol

wuyo2

Aug 8, 2024

GGUF!!!! ㅠㅠ

ywjung

Aug 8, 2024

If it's public, please provide the gguf format so I can try it, or change it to a license that allows me to convert it. ㅠㅠㅠㅠㅠㅠ

LG-AI-EXAONE

LG AI Research org Aug 8, 2024

We have revised our license according to your requests. Please check the new license

yireun

Aug 13, 2024

You can llamafy EXAONE by referring to the followings. Thanks to maywell and CarrotAI.
- maywell/EXAONE-3.0-7.8B-Instruct-Llamafied
- CarrotAI/EXAONE-3.0-7.8B-Instruct-Llamafied-cpu
You can resolve the issues that occur when converting the above EXAONE-Llamafied to GGUF format and inferencing the converted GGUF using llama.cpp by referring to the following.
- https://huggingface.co/LGAI-EXAONE/EXAONE-3.0-7.8B-Instruct/discussions/8

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