Instructions to use tiiuae/Falcon3-3B-Base with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use tiiuae/Falcon3-3B-Base with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-generation", model="tiiuae/Falcon3-3B-Base")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForCausalLM tokenizer = AutoTokenizer.from_pretrained("tiiuae/Falcon3-3B-Base") model = AutoModelForCausalLM.from_pretrained("tiiuae/Falcon3-3B-Base", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- vLLM
How to use tiiuae/Falcon3-3B-Base with vLLM:
Install from pip and serve model
# Install vLLM from pip: pip install vllm # Start the vLLM server: vllm serve "tiiuae/Falcon3-3B-Base" # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:8000/v1/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "tiiuae/Falcon3-3B-Base", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }'Use Docker
docker model run hf.co/tiiuae/Falcon3-3B-Base
- SGLang
How to use tiiuae/Falcon3-3B-Base 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 "tiiuae/Falcon3-3B-Base" \ --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": "tiiuae/Falcon3-3B-Base", "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 "tiiuae/Falcon3-3B-Base" \ --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": "tiiuae/Falcon3-3B-Base", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }' - Docker Model Runner
How to use tiiuae/Falcon3-3B-Base with Docker Model Runner:
docker model run hf.co/tiiuae/Falcon3-3B-Base
Commit History
-
Fix typo in Minitron GPQA score.
Verified signature092c29e
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Update README.md (#4)
Verified signature- Update README.md (3f8f72b208b4a7d1baa59b3b88f3e7b5a7cc6b92) Co-authored-by: Abdalgader Abubaker <Abdalgader@users.noreply.huggingface.co>0d42fd1 -
Updating the tags in the README (#3)
Verified signature- Updating the tags in the README (d969d6f6ee69ba7b309a7940239f58647c9d558d) - Update README.md (c5251cc93147663fd450a3e183eb580b70807c6f) Co-authored-by: Aritra Roy Gosthipaty <ariG23498@users.noreply.huggingface.co>a34ae37 -
falcon3 release
slim.frikha9b96498