Create README.md

README.md

@@ -0,0 +1,137 @@
+---
+library_name: transformers
+tags:
+- falcon-h1
+license: other
+license_name: falcon-llm-license
+license_link: https://falconllm.tii.ae/falcon-terms-and-conditions.html
+---
+
+#  Table of Contents
+
+0. [TL;DR](#TL;DR)
+1. [Model Details](#model-details)
+2. [Training Details](#training-details)
+3. [Usage](#usage)
+4. [Evaluation](#evaluation)
+5. [Citation](#citation)
+
+# TL;DR
+
+# Model Details
+
+## Model Description
+
+- **Developed by:** [https://www.tii.ae](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](https://falcon-lm.github.io/blog/falcon-h1/).
+
+# Usage
+
+Currently to use this model you can either rely on Hugging Face `transformers`, `vLLM` or our custom fork of `llama.cpp` library.
+
+## Inference
+
+Make sure to install the latest version of `transformers` or `vllm`, eventually install these packages from source:
+
+```bash
+pip install git+https://github.com/huggingface/transformers.git
+```
+
+Refer to [the official vLLM documentation for more details on building vLLM from source](https://docs.vllm.ai/en/latest/getting_started/installation/gpu.html#build-wheel-from-source).
+
+### 🤗 transformers
+
+Refer to the snippet below to run H1 models using 🤗 transformers:
+
+```python
+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
+```
+
+### `llama.cpp`
+
+While we are working on integrating our architecture directly into `llama.cpp` library, 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`.
+
+# Evaluation
+
+Falcon-H1 series perform very well on a variety of tasks, including reasoning tasks. 
+
+| Tasks | Falcon-H1-3B | Qwen3-4B | Qwen2.5-3B | Gemma3-4B | Llama3.2-3B | Falcon3-3B |
+| --- | --- | --- | --- | --- | --- | --- |
+| **General**  | | | | | |
+| BBH | **53.69** | 51.07 | 46.55 | 50.01 | 41.47 | 45.02 |
+| ARC-C | **49.57** | 37.71 | 43.77 | 44.88 | 44.88 | 48.21 |
+| TruthfulQA | 53.19 | 51.75 | **58.11** | 51.68 | 50.27 | 50.06 |
+| HellaSwag | **69.85** | 55.31 | 64.21 | 47.68 | 63.74 | 64.24 |
+| MMLU | **68.3** | 67.01 | 65.09 | 59.53 | 61.74 | 56.76 |
+| **Math**  | | | | | |
+| GSM8k | **84.76** | 80.44 | 57.54 | 77.41 | 77.26 | 74.68 |
+| MATH-500 | 74.2 | **85.0** | 64.2 | 76.4 | 41.2 | 54.2 |
+| AMC-23 | 55.63 | **66.88** | 39.84 | 48.12 | 22.66 | 29.69 |
+| AIME-24 | 11.88 | **22.29** | 6.25 | 6.67 | 11.67 | 3.96 |
+| AIME-25 | 13.33 | **18.96** | 3.96 | 13.33 | 0.21 | 2.29 |
+| **Science**  | | | | | |
+| GPQA | **33.89** | 28.02 | 28.69 | 29.19 | 28.94 | 28.69 |
+| GPQA_Diamond | 38.72 | **40.74** | 35.69 | 28.62 | 29.97 | 29.29 |
+| MMLU-Pro | **43.69** | 29.75 | 32.76 | 29.71 | 27.44 | 29.71 |
+| MMLU-stem | **69.93** | 67.46 | 59.78 | 52.17 | 51.92 | 56.11 |
+| **Code**  | | | | | |
+| HumanEval | 76.83 | **84.15** | 73.78 | 67.07 | 54.27 | 52.44 |
+| HumanEval+ | 70.73 | **76.83** | 68.29 | 61.59 | 50.0 | 45.73 |
+| MBPP | **79.63** | 68.78 | 72.75 | 77.78 | 62.17 | 61.9 |
+| MBPP+ | **67.46** | 59.79 | 60.85 | 66.93 | 50.53 | 55.29 |
+| LiveCodeBench | 26.81 | **39.92** | 11.74 | 21.14 | 2.74 | 3.13 |
+| CRUXEval | 56.25 | **69.63** | 43.26 | 52.13 | 17.75 | 44.38 |
+| **Instruction Following**  | | | | | |
+| IFEval | **85.05** | 84.01 | 64.26 | 77.01 | 74.0 | 69.1 |
+| Alpaca-Eval | 31.09 | 36.51 | 17.37 | **39.64** | 19.69 | 14.82 |
+| MTBench | **8.72** | 8.45 | 7.79 | 8.24 | 7.96 | 7.79 |
+| LiveBench | 36.86 | **51.34** | 27.32 | 36.7 | 26.37 | 26.01 |
+
+You can check more in detail on our [our release blogpost](https://falcon-lm.github.io/blog/falcon-h1/), detailed benchmarks.
+
+# Useful links
+
+- View [our release blogpost](https://falcon-lm.github.io/blog/falcon-h1/).
+- Feel free to join [our discord server](https://discord.gg/fwXpMyGc) if you have any questions or to interact with our researchers and developers.
+
+# 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}
+}
+```