Instructions to use meta-llama/Llama-3.1-8B with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

Libraries

How to use meta-llama/Llama-3.1-8B with Transformers:

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

pipe = pipeline("text-generation", model="meta-llama/Llama-3.1-8B")

# Load model directly
from transformers import AutoTokenizer, AutoModelForCausalLM

tokenizer = AutoTokenizer.from_pretrained("meta-llama/Llama-3.1-8B")
model = AutoModelForCausalLM.from_pretrained("meta-llama/Llama-3.1-8B")

Inference
Notebooks
Google Colab
Kaggle
Local Apps

vLLM

How to use meta-llama/Llama-3.1-8B with vLLM:

Install from pip and serve model

# Install vLLM from pip:
pip install vllm
# Start the vLLM server:
vllm serve "meta-llama/Llama-3.1-8B"
# Call the server using curl (OpenAI-compatible API):
curl -X POST "http://localhost:8000/v1/completions" \
	-H "Content-Type: application/json" \
	--data '{
		"model": "meta-llama/Llama-3.1-8B",
		"prompt": "Once upon a time,",
		"max_tokens": 512,
		"temperature": 0.5
	}'

Use Docker

docker model run hf.co/meta-llama/Llama-3.1-8B

SGLang

How to use meta-llama/Llama-3.1-8B 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 "meta-llama/Llama-3.1-8B" \
    --host 0.0.0.0 \
    --port 30000
# Call the server using curl (OpenAI-compatible API):
curl -X POST "http://localhost:30000/v1/completions" \
	-H "Content-Type: application/json" \
	--data '{
		"model": "meta-llama/Llama-3.1-8B",
		"prompt": "Once upon a time,",
		"max_tokens": 512,
		"temperature": 0.5
	}'

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 "meta-llama/Llama-3.1-8B" \
        --host 0.0.0.0 \
        --port 30000
# Call the server using curl (OpenAI-compatible API):
curl -X POST "http://localhost:30000/v1/completions" \
	-H "Content-Type: application/json" \
	--data '{
		"model": "meta-llama/Llama-3.1-8B",
		"prompt": "Once upon a time,",
		"max_tokens": 512,
		"temperature": 0.5
	}'

Docker Model Runner
How to use meta-llama/Llama-3.1-8B with Docker Model Runner:
```
docker model run hf.co/meta-llama/Llama-3.1-8B
```

Access request FAQ

#21

pinned

by samuelselvan - opened Jul 30, 2024

Discussion

samuelselvan

Jul 30, 2024

How do I get the models?

You can get the Meta Llama models directly from Meta or through Hugging Face or Kaggle. However you get the models, you will first need to accept the license agreements for the models you want.

How do I obtain the models from Hugging Face?

Please sign into your account and select the models you want. You will be taken to a page where you can fill in your information and review the appropriate license agreement.

What if I want to access Llama models but I’m not sure if my use is permitted under the Llama Community License?

Please contact llamamodels@meta.com to provide more details about your request.

Why is it taking so long to get my approval?

After accepting the agreement, your information is reviewed; the review process could take up to a few days. When you are approved, you will receive an email informing you that you have access to the HF repository for the model. All approved and not approved emails are sent to the email you used to sign up, please make sure you are using the same email.

Why was my request rejected?

Meta Llama 3 is available via HuggingFace globally, except in comprehensively sanctioned jurisdictions.

Why I am not able to access from China/Russia?

Meta Llama 3 is available via HuggingFace globally, except in comprehensively sanctioned jurisdictions.

Why is download blocked in China/Russia?

Meta Llama 3 is available via HuggingFace globally, except in comprehensively sanctioned jurisdictions.

samuelselvan pinned discussion Jul 30, 2024

samuelselvan locked this discussion Jul 30, 2024

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