Instructions to use tiiuae/Falcon3-7B-Base with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use tiiuae/Falcon3-7B-Base with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-generation", model="tiiuae/Falcon3-7B-Base")# Load model directly from transformers import AutoTokenizer, AutoModelForCausalLM tokenizer = AutoTokenizer.from_pretrained("tiiuae/Falcon3-7B-Base") model = AutoModelForCausalLM.from_pretrained("tiiuae/Falcon3-7B-Base") - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- vLLM
How to use tiiuae/Falcon3-7B-Base with vLLM:
Install from pip and serve model
# Install vLLM from pip: pip install vllm # Start the vLLM server: vllm serve "tiiuae/Falcon3-7B-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/Falcon3-7B-Base", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }'Use Docker
docker model run hf.co/tiiuae/Falcon3-7B-Base
- SGLang
How to use tiiuae/Falcon3-7B-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/Falcon3-7B-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/Falcon3-7B-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/Falcon3-7B-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/Falcon3-7B-Base", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }' - Docker Model Runner
How to use tiiuae/Falcon3-7B-Base with Docker Model Runner:
docker model run hf.co/tiiuae/Falcon3-7B-Base
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# Benchmarks
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We report in the following table our internal pipeline benchmarks.
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- We use [lm-evaluation harness](https://github.com/EleutherAI/lm-evaluation-harness).
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- We report **raw scores**.
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- View our [release blogpost](https://huggingface.co/blog/falcon3).
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- Feel free to join [our discord server](https://discord.gg/fwXpMyGc) if you have any questions or to interact with our researchers and developers.
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#
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If Falcon3 family were helpful to your work, feel free to give us a cite.
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```
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<br>
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## Benchmarks
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We report in the following table our internal pipeline benchmarks.
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- We use [lm-evaluation harness](https://github.com/EleutherAI/lm-evaluation-harness).
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- We report **raw scores**.
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- View our [release blogpost](https://huggingface.co/blog/falcon3).
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- Feel free to join [our discord server](https://discord.gg/fwXpMyGc) if you have any questions or to interact with our researchers and developers.
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## Technical Report
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Coming soon....
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## Citation
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If Falcon3 family were helpful to your work, feel free to give us a cite.
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```
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