Instructions to use meta-llama/Llama-3.2-3B with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

Libraries

How to use meta-llama/Llama-3.2-3B with Transformers:

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

pipe = pipeline("text-generation", model="meta-llama/Llama-3.2-3B")

# Load model directly
from transformers import AutoTokenizer, AutoModelForCausalLM

tokenizer = AutoTokenizer.from_pretrained("meta-llama/Llama-3.2-3B")
model = AutoModelForCausalLM.from_pretrained("meta-llama/Llama-3.2-3B")

Inference
Notebooks
Google Colab
Kaggle
Local Apps

vLLM

How to use meta-llama/Llama-3.2-3B with vLLM:

Install from pip and serve model

# Install vLLM from pip:
pip install vllm
# Start the vLLM server:
vllm serve "meta-llama/Llama-3.2-3B"
# 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-3.2-3B",
		"prompt": "Once upon a time,",
		"max_tokens": 512,
		"temperature": 0.5
	}'

Use Docker

docker model run hf.co/meta-llama/Llama-3.2-3B

SGLang

How to use meta-llama/Llama-3.2-3B 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-3.2-3B" \
    --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-3.2-3B",
		"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-3.2-3B" \
        --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-3.2-3B",
		"prompt": "Once upon a time,",
		"max_tokens": 512,
		"temperature": 0.5
	}'

Docker Model Runner
How to use meta-llama/Llama-3.2-3B with Docker Model Runner:
```
docker model run hf.co/meta-llama/Llama-3.2-3B
```

Request to re-evaluate access for [dr777] - Research on Neuroscience Visualization

#68

by dr777 - opened Mar 30

Discussion

dr777

Mar 30

•

edited Mar 30

Hi Llama/Meta Team,

My Meta Request ID: 1517269096586383

I am writing to request a re-evaluation of my access to this model. My previous application might have been overlooked or contained incomplete information.
My Background:
I am a developer and researcher specializing in the intersection of Artificial Intelligence and Neuroscience.
Project Goal:
I am currently working on a high-precision 3D brain structure reconstruction project and developing a research platform that integrates neural data with interactive visualization (Unity/WebGL). This model is crucial for my research on brain modeling and medical simulation.
Commitment:
I fully agree to the Llama 3.2 Community License / Meta's terms and will only use the model for research and development purposes as outlined in the agreement.
Could you please reset my application status or grant me access?
My Hugging Face ID: [dr777]
Email: [191428272@qq.com]
Thank you for your time and support!

Upload images, audio, and videos by dragging in the text input, pasting, or clicking here.

Tap or paste here to upload images

· Sign up or log in to comment