README.md

---
language:
- en
- fr
- es
- pt
tags:
- falcon3
---

# Falcon3-10B-Base

**Falcon3** family of Open Foundation Models is a set of pretrained and instruct LLMs ranging from 1B to 10B.

This repository contains the **Falcon3-10B-Base**. It achieves state of art results (at release's time) on reasoning, language understanding, instruction following, code and mathematics tasks.
Falcon3-10B-Base supports 4 languages (english, french, spanish, portuguese) and a context length up to 32K.

⚠️ **This is a raw, pretrained model, which should be further finetuned for most usecases.** 

## Model Details
- Architecture
  - transformer based causal decoder only architecture
  - 40 decoder blocks
  - grouped query attention (GQA) for faster inference: 12 query heads and 4 KV heads
  - wider head dimension: 256
  - high RoPE value to support long context understanding: 1000042
  - 32k context length
  - 131k vocab size
- Depth-up-scaled from **Falcon3-7B-Base** with 2 Gigatokens of datasets comprising of web, code, STEM, high quality and mutlilingual data using 2048 H100 GPU chips
- Supports EN, FR, ES, PT
- Developed by [Technology Innovation Institute](https://www.tii.ae)
- License: TII Falcon-LLM License 2.0
- Model Release Date: December 2024


## Getting started

<details>
<summary> Click to expand </summary>

```python
import torch
from transformers import pipeline

pipe = pipeline(
    "text-generation", 
    model="tiiuae/Falcon3-10B-Base", 
    torch_dtype=torch.bfloat16, 
    device_map="auto"
)
response = pipe("Question: How many hours in one day? Answer: ")
print(response[0]['generated_text'])
```

</details>

<br>

# Benchmarks
We report in the following table our internal pipeline benchmarks:

<table border="1" style="width: 100%; text-align: center; border-collapse: collapse;">
    <colgroup>
        <col style="width: 10%;">
        <col style="width: 10%;">
        <col style="width: 7%;">
        <col style="width: 7%;">
        <col style="width: 7%;">
        <col style="background-color: rgba(80, 15, 213, 0.5); width: 7%;">
    </colgroup>
    <thead>
        <tr>
            <th>Category</th>
            <th>Benchmark</th>
            <th>Gemma2-9B</th>
            <th>Yi1.5-9B</th>
            <th>Mistral-NeMo-12B</th>
            <th>Falcon3-10B-Base</th>
        </tr>
    </thead>
    <tbody>
        <tr>
            <td rowspan="3">General</td>
            <td>MMLU (5-shot)</td>
            <td>0</td>
            <td>69.6</td>
            <td>68.8</td>
            <td>73.1</td>
        </tr>
        <tr>
            <td>MMLU-PRO (5-shot)</td>
            <td>0</td>
            <td>39.3</td>
            <td>34.7</td>
            <td>42.5</td>
        </tr>
        <tr>
            <td>IFEval</td>
            <td>0</td>
            <td>29.1</td>
            <td>16.1</td>
            <td>36.4</td>
        </tr>
        <tr>
            <td rowspan="2">Math</td>
            <td>GSM8K (5-shot)</td>
            <td>69.1</td>
            <td>63.8</td>
            <td>55.3</td>
            <td>81.4</td>
        </tr>
        <tr>
            <td>MATH(4-shot)</td>
            <td>0</td>
            <td>9.2</td>
            <td>4.9</td>
            <td>22.9</td>
        </tr>
        <tr>
            <td rowspan="4">Reasoning</td>
            <td>Arc Challenge (25-shot)</td>
            <td>63.7</td>
            <td>58.2</td>
            <td>60.6</td>
            <td>62.6</td>
        </tr>
        <tr>
            <td>GPQA (0-shot)</td>
            <td>0</td>
            <td>36.6</td>
            <td>28.8</td>
            <td>34.1</td>
        </tr>
        <tr>
            <td>MUSR (0-shot)</td>
            <td>0</td>
            <td>43.3</td>
            <td>39.2</td>
            <td>44.2</td>
        </tr>
        <tr>
            <td>BBH (3-shot)</td>
            <td>0</td>
            <td>51.3</td>
            <td>50.2</td>
            <td>59.7</td>
        </tr>
        <tr>
            <td rowspan="4">CommonSense Understanding</td>
            <td>PIQA (0-shot)</td>
            <td>81.4</td>
            <td>79.8</td>
            <td>81.4</td>
            <td>79.1</td>
        </tr>
        <tr>
            <td>SciQ (0-shot)</td>
            <td>97.2</td>
            <td>95.8</td>
            <td>96.4</td>
            <td>96.0</td>
        </tr>
        <tr>
            <td>Winogrande (0-shot)</td>
            <td>74.2</td>
            <td>72.7</td>
            <td>73.2</td>
            <td>73.6</td>
        </tr>
        <tr>
            <td>OpenbookQA (0-shot)</td>
            <td>34.0</td>
            <td>35.4</td>
            <td>36.4</td>
            <td>34.0</td>
        </tr>
    </tbody>
</table>



# Citation
If Falcon3 family were helpful to your work, feel free to give us a cite.

```
@misc{Falcon3,
    title = {Falcon 3 family of Open Foundation Models},
    author = {TII Team},
    month = {December},
    year = {2024}
}
```