Instructions to use meta-llama/Llama-3.2-3B-Instruct with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use meta-llama/Llama-3.2-3B-Instruct 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-Instruct") messages = [ {"role": "user", "content": "Who are you?"}, ] pipe(messages)# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForCausalLM tokenizer = AutoTokenizer.from_pretrained("meta-llama/Llama-3.2-3B-Instruct") model = AutoModelForCausalLM.from_pretrained("meta-llama/Llama-3.2-3B-Instruct", device_map="auto") messages = [ {"role": "user", "content": "Who are you?"}, ] inputs = tokenizer.apply_chat_template( messages, add_generation_prompt=True, tokenize=True, return_dict=True, return_tensors="pt", ).to(model.device) outputs = model.generate(**inputs, max_new_tokens=256) print(tokenizer.decode(outputs[0][inputs["input_ids"].shape[-1]:])) - Inference
- Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- vLLM
How to use meta-llama/Llama-3.2-3B-Instruct 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-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": "meta-llama/Llama-3.2-3B-Instruct", "messages": [ { "role": "user", "content": "What is the capital of France?" } ] }'Use Docker
docker model run hf.co/meta-llama/Llama-3.2-3B-Instruct
- SGLang
How to use meta-llama/Llama-3.2-3B-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 "meta-llama/Llama-3.2-3B-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": "meta-llama/Llama-3.2-3B-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 "meta-llama/Llama-3.2-3B-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": "meta-llama/Llama-3.2-3B-Instruct", "messages": [ { "role": "user", "content": "What is the capital of France?" } ] }' - Docker Model Runner
How to use meta-llama/Llama-3.2-3B-Instruct with Docker Model Runner:
docker model run hf.co/meta-llama/Llama-3.2-3B-Instruct
Request to reset the Llama-3.2-3B-Instruct Application
Dear Meta Llama Team,
My request for access to meta-llama/Llama-3.2-3B-Instruct was recently denied. I believe this may have been due to inaccurate or incomplete information I provided when submitting my application.
This was my first time requesting access to a model on Hugging Face. I mistakenly assumed it was a routine registration process and did not complete the form with the care it required. I sincerely apologize for this oversight.
I am a student currently studying natural language processing and large language models. I am also taking the Hugging Face Agents Course and would like to use Llama 3.2 3B Instruct for educational purposes and non-commercial research.
I am happy to provide accurate and complete information and am committed to complying with the Llama 3.2 Community License Agreement and Acceptable Use Policy.
I would greatly appreciate it if you could reconsider my request or reset its status so that I can submit a new application with the correct information.
My Hugging Face username is Shamxisa.
Thank you for your time and consideration.
Best regards,
SHAMXISA