Falcon H1 3B Base

🚀 Falcon-H1 Model

The Falcon-H1 series is a family of hybrid-head language models developed by TII, offering high efficiency and performance across various tasks.

🚀 Quick Start

Currently, to use this model, you can rely on Hugging Face transformers, vLLM, or our custom fork of the llama.cpp library.

✨ Features

• Model Type: Causal decoder - only
• Architecture: Hybrid Transformers + Mamba architecture
• Language(s) (NLP): English, Multilingual
• License: Falcon - LLM License

📦 Installation

Install transformers

Make sure to install the latest version of transformers, and you can install it from source:

pip install git+https://github.com/huggingface/transformers.git

Refer to the official vLLM documentation for more details on building vLLM from source.

Install vLLM

pip install vLLM

Install llama.cpp

You can install our fork of the library and use it directly: https://github.com/tiiuae/llama.cpp - Falcon - H1. Use the same installing guidelines as llama.cpp.

💻 Usage Examples

Basic Usage

🤗 transformers

Refer to the snippet below to run H1 models using 🤗 transformers:

import torch
from transformers import AutoModelForCausalLM, AutoTokenizer

model_id = "tiiuae/Falcon-H1-1B-Base"

model = AutoModelForCausalLM.from_pretrained(
  model_id,
  torch_dtype=torch.bfloat16,
  device_map="auto"
)

# Perform text generation

vLLM

For vLLM, simply start a server by executing the command below:

# pip install vllm
vllm serve tiiuae/Falcon-H1-1B-Instruct --tensor-parallel-size 2 --data-parallel-size 1

Advanced Usage

While we are working on integrating our architecture directly into the llama.cpp library, you can use our custom fork as described in the installation section.

📚 Documentation

Model Details

• Developed by: https://www.tii.ae
• Model type: Causal decoder - only
• Architecture: Hybrid Transformers + Mamba architecture
• Language(s) (NLP): English, Multilingual
• License: Falcon - LLM License

Training Details

For more details about the training protocol of this model, please refer to the Falcon - H1 technical blogpost.

Evaluation

Falcon - H1 series perform very well on a variety of tasks, including reasoning tasks.

You can check more in - detail on our our release blogpost, detailed benchmarks.

Useful Links

• View our release blogpost.
• Feel free to join our discord server if you have any questions or to interact with our researchers and developers.

📄 License

This model is licensed under the Falcon - LLM License.

📚 Citation

If the Falcon - H1 family of models were helpful to your work, feel free to give us a cite.

@misc{tiifalconh1,
    title = {Falcon-H1: A Family of Hybrid-Head Language Models Redefining Efficiency and Performance},
    url = {https://falcon-lm.github.io/blog/falcon-h1},
    author = {Falcon-LLM Team},
    month = {May},
    year = {2025}
}