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+ ---
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+ library_name: transformers
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+ tags:
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+ - falcon-h1
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+ - unsloth
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+ license: other
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+ license_name: falcon-llm-license
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+ license_link: https://falconllm.tii.ae/falcon-terms-and-conditions.html
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+ base_model:
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+ - tiiuae/Falcon-H1-1.5B-Deep-Instruct
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+ inference: true
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+ ---
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+ > [!NOTE]
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+ > Includes our **chat template fixes**! <br> For `llama.cpp`, use `--jinja`
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+ >
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+
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+ <div>
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+ <p style="margin-top: 0;margin-bottom: 0;">
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+ <em><a href="https://docs.unsloth.ai/basics/unsloth-dynamic-v2.0-gguf">Unsloth Dynamic 2.0</a> achieves superior accuracy & outperforms other leading quants.</em>
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+ </p>
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+ <div style="display: flex; gap: 5px; align-items: center; ">
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+ <a href="https://github.com/unslothai/unsloth/">
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+ <img src="https://github.com/unslothai/unsloth/raw/main/images/unsloth%20new%20logo.png" width="133">
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+ </a>
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+ <a href="https://discord.gg/unsloth">
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+ <img src="https://github.com/unslothai/unsloth/raw/main/images/Discord%20button.png" width="173">
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+ </a>
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+ <a href="https://docs.unsloth.ai/">
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+ <img src="https://raw.githubusercontent.com/unslothai/unsloth/refs/heads/main/images/documentation%20green%20button.png" width="143">
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+ </a>
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+ </div>
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+ </div>
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+
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+
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+ <img src="https://huggingface.co/datasets/tiiuae/documentation-images/resolve/main/falcon_mamba/falcon-h1-logo.png" alt="drawing" width="800"/>
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+
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+ # Table of Contents
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+
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+ 0. [TL;DR](#TL;DR)
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+ 1. [Model Details](#model-details)
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+ 2. [Training Details](#training-details)
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+ 3. [Usage](#usage)
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+ 4. [Evaluation](#evaluation)
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+ 5. [Citation](#citation)
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+
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+ # TL;DR
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+
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+ # Model Details
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+
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+ ## Model Description
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+
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+ - **Developed by:** [https://www.tii.ae](https://www.tii.ae)
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+ - **Model type:** Causal decoder-only
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+ - **Architecture:** Hybrid Transformers + Mamba architecture
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+ - **Language(s) (NLP):** English, Multilingual
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+ - **License:** Falcon-LLM License
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+
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+ # Training details
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+
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+ For more details about the training protocol of this model, please refer to the [Falcon-H1 technical blogpost](https://falcon-lm.github.io/blog/falcon-h1/).
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+
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+ # Usage
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+
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+ Currently to use this model you can either rely on Hugging Face `transformers`, `vLLM` or `llama.cpp` library.
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+
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+ ## Inference
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+
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+ Make sure to install the latest version of `transformers` or `vllm`, eventually install these packages from source:
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+
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+ ```bash
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+ pip install git+https://github.com/huggingface/transformers.git
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+ ```
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+
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+ For vLLM, make sure to install `vllm>=0.9.0`:
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+
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+ ```bash
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+ pip install "vllm>=0.9.0"
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+ ```
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+ ### 🤗 transformers
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+
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+ Refer to the snippet below to run H1 models using 🤗 transformers:
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+
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+ ```python
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+ import torch
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+ from transformers import AutoModelForCausalLM, AutoTokenizer
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+
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+ model_id = "tiiuae/Falcon-H1-1B-Base"
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+
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+ model = AutoModelForCausalLM.from_pretrained(
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+ model_id,
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+ torch_dtype=torch.bfloat16,
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+ device_map="auto"
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+ )
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+
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+ # Perform text generation
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+ ```
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+
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+ ### vLLM
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+
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+ For vLLM, simply start a server by executing the command below:
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+
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+ ```
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+ # pip install vllm>=0.9.0
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+ vllm serve tiiuae/Falcon-H1-1B-Instruct --tensor-parallel-size 2 --data-parallel-size 1
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+ ```
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+
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+ ### `llama.cpp`
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+
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+ You can find all GGUF files compatible with `llama.cpp` under [our official collection](https://huggingface.co/collections/tiiuae/falcon-h1-6819f2795bc406da60fab8df)
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+
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+ # Evaluation
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+
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+ Falcon-H1 series perform very well on a variety of tasks, including reasoning tasks.
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+
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+ | Tasks | Falcon-H1-1.5B-deep | Qwen3-1.7B | Qwen2.5-1.5B | Gemma3-1B | Llama3.2-1B | Falcon3-1B |
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+ | --- | --- | --- | --- | --- | --- | --- |
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+ | **General** | | | | | |
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+ | BBH | **54.43** | 35.18 | 42.41 | 35.86 | 33.21 | 34.47 |
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+ | ARC-C | **43.86** | 34.81 | 40.53 | 34.13 | 34.64 | 43.09 |
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+ | TruthfulQA | **50.48** | 49.39 | 47.05 | 42.17 | 42.08 | 42.31 |
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+ | HellaSwag | **65.54** | 49.27 | 62.23 | 42.24 | 55.3 | 58.53 |
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+ | MMLU | **66.11** | 57.04 | 59.76 | 40.87 | 45.93 | 46.1 |
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+ | **Math** | | | | | |
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+ | GSM8k | **82.34** | 69.83 | 57.47 | 42.38 | 44.28 | 44.05 |
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+ | MATH-500 | **77.8** | 73.0 | 48.4 | 45.4 | 13.2 | 19.8 |
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+ | AMC-23 | **56.56** | 46.09 | 24.06 | 19.22 | 7.19 | 6.87 |
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+ | AIME-24 | **14.37** | 12.5 | 2.29 | 0.42 | 1.46 | 0.41 |
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+ | AIME-25 | **11.04** | 8.12 | 1.25 | 1.25 | 0.0 | 0.21 |
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+ | **Science** | | | | | |
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+ | GPQA | **33.22** | 27.68 | 26.26 | 28.19 | 26.59 | 26.76 |
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+ | GPQA_Diamond | **40.57** | 33.33 | 25.59 | 21.55 | 25.08 | 31.31 |
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+ | MMLU-Pro | **41.89** | 23.54 | 28.35 | 14.46 | 16.2 | 18.49 |
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+ | MMLU-stem | **67.3** | 54.3 | 54.04 | 35.39 | 39.16 | 39.64 |
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+ | **Code** | | | | | |
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+ | HumanEval | **73.78** | 67.68 | 56.1 | 40.85 | 34.15 | 22.56 |
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+ | HumanEval+ | **68.9** | 60.96 | 50.61 | 37.2 | 29.88 | 20.73 |
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+ | MBPP | **68.25** | 58.73 | 64.81 | 57.67 | 33.6 | 20.63 |
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+ | MBPP+ | **56.61** | 49.74 | 56.08 | 50.0 | 29.37 | 17.2 |
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+ | LiveCodeBench | **23.87** | 14.87 | 12.52 | 5.09 | 2.35 | 0.78 |
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+ | CRUXEval | **52.32** | 18.88 | 34.76 | 12.7 | 0.06 | 15.58 |
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+ | **Instruction Following** | | | | | |
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+ | IFEval | **83.5** | 70.77 | 45.33 | 61.48 | 55.34 | 54.26 |
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+ | Alpaca-Eval | **27.12** | 21.89 | 9.54 | 17.87 | 9.38 | 6.98 |
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+ | MTBench | **8.53** | 7.61 | 7.1 | 7.03 | 6.37 | 6.03 |
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+ | LiveBench | 36.83 | **40.73** | 21.65 | 18.79 | 14.97 | 14.1 |
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+
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+ You can check more in detail on our [our release blogpost](https://falcon-lm.github.io/blog/falcon-h1/), detailed benchmarks.
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+
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+ # Useful links
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+
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+ - View [our release blogpost](https://falcon-lm.github.io/blog/falcon-h1/).
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+ - Feel free to join [our discord server](https://discord.gg/trwMYP9PYm) if you have any questions or to interact with our researchers and developers.
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+
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+ # Citation
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+
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+ If the Falcon-H1 family of models were helpful to your work, feel free to give us a cite.
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+
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+ ```
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+ @misc{tiifalconh1,
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+ title = {Falcon-H1: A Family of Hybrid-Head Language Models Redefining Efficiency and Performance},
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+ url = {https://falcon-lm.github.io/blog/falcon-h1},
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+ author = {Falcon-LLM Team},
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+ month = {May},
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+ year = {2025}
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+ }
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+ ```