add scores for 1B
#3
by
wdevazelhes
- opened
- README.md +87 -136
- tokenizer_config.json +1 -1
README.md
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@@ -7,21 +7,16 @@ language:
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tags:
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- falcon3
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base_model: tiiuae/Falcon3-7B-Base
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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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library_name: transformers
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---
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<div align="center">
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<img src="https://huggingface.co/datasets/tiiuae/documentation-images/resolve/main/general/falco3-logo.png" alt="drawing" width="500"/>
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</div>
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# Falcon3-7B-Instruct
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**Falcon3** family of Open Foundation Models is a set of pretrained and instruct LLMs ranging from 1B to 10B.
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This repository contains the **Falcon3-7B-Instruct**. It achieves state of art results (at
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Falcon3-7B-Instruct supports 4 languages (english, french, spanish, portuguese) and a context length up to 32K.
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## Model Details
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- Uses SwiGLU and RMSNorm
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- 32K context length
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- 131K vocab size
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- Pretrained on 14 Teratokens of datasets comprising of web, code, STEM, high quality and mutlilingual data using
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- Postrained on 1.2 million samples of STEM, conversations, code, safety and function call data
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- Supports EN, FR, ES, PT
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- Developed by [Technology Innovation Institute](https://www.tii.ae)
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<br>
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## Benchmarks
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We report the
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<table border="1" style="width: 100%; text-align: center; border-collapse: collapse;">
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<colgroup>
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<col style="width: 10%;">
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<col style="width: 7%;">
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<col style="width: 7%;">
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<col style="background-color: rgba(80, 15, 213, 0.5); width: 7%;">
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</colgroup>
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<thead>
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<tr>
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<th>Benchmark</th>
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<th>Llama-3.1-8B-Instruct</th>
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<th>Qwen2.5-7B-Instruct</th>
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<th>Falcon3-7B-Instruct</th>
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</tr>
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</thead>
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<tbody>
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<tr>
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<td>IFEval</td>
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<td><b>78.56</b></td>
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<td>75.85</td>
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<td>76.12</td>
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</tr>
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<tr>
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<td>BBH (3-shot)</td>
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<td>29.89</td>
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<td>34.89</td>
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<td><b>37.92</b></td>
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</tr>
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<tr>
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<td>MATH Lvl-5 (4-shot)</td>
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<td>19.34</td>
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<td>0.00</td>
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<td><b>31.87</b></td>
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</tr>
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<tr>
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<td>GPQA (0-shot)</td>
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<td>2.35</td>
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<td>5.48</td>
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<td><b>8.05</b></td>
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</tr>
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<tr>
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<td>MUSR (0-shot)</td>
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<td>8.41</td>
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<td>8.45</td>
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<td><b>21.17</b></td>
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</tr>
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<tr>
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<td>MMLU-PRO (5-shot)</td>
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<td>30.68</td>
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<td><b>36.52</b></td>
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<td>34.30</td>
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</tr>
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</tbody>
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</table>
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Also, 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** obtained by applying chat template and fewshot_as_multiturn.
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- We use same batch-size across all models.
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<table border="1" style="width: 100%; text-align: center; border-collapse: collapse;">
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<colgroup>
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<col style="width: 10%;">
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<col style="width: 7%;">
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<col style="width: 7%;">
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<col style="background-color: rgba(80, 15, 213, 0.5); width: 7%;">
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</colgroup>
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<thead>
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<tr>
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<th>Category</th>
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<th>Benchmark</th>
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<th>Llama-3.
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<th>Qwen2.5-
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<th>
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</tr>
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</thead>
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<tbody>
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<tr>
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<td rowspan="3">General</td>
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<td>MMLU (5-shot)</td>
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<td>
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<td><b>
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</tr>
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<tr>
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<td>MMLU-PRO (5-shot)</td>
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<td>
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<td><b>
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<td>
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</tr>
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<tr>
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<td>IFEval</td>
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<td><b>
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</tr>
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<tr>
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<td rowspan="3">Math</td>
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<td>GSM8K (5-shot)</td>
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<td
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<td>
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<td>
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</tr>
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<tr>
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<td>GSM8K (8-shot, COT)</td>
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<td
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<td>
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</tr>
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<tr>
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<td>MATH Lvl-5 (4-shot)</td>
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<td>
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<td
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<td
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</tr>
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<tr>
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<td rowspan="
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<td>Arc Challenge (25-shot)</td>
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<td>
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<td>
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<td><b>
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</tr>
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<tr>
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<td>GPQA (0-shot)</td>
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<td
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<td>
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</tr>
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<tr>
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<td>GPQA (0-shot, COT)</td>
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<td>
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<td>
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<td
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</tr>
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<tr>
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<td>MUSR (0-shot)</td>
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<td>
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<td
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</tr>
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<tr>
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<td>BBH (3-shot)</td>
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<td><b>
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<td>
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</tr>
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<tr>
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<td rowspan="
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<td>PIQA (0-shot)</td>
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<td
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<td>73.
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<td>
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</tr>
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<tr>
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<td>SciQ (0-shot)</td>
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<td>
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<td>
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<td
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</tr>
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<tr>
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<td>Winogrande (0-shot)</td>
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<td>-</td>
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<td>-</td>
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<td
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</tr>
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<tr>
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<td>OpenbookQA (0-shot)</td>
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</tr>
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<tr>
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<td rowspan="2">Instructions following</td>
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<td>MT-Bench (avg)</td>
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<td>
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<td><b>
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<td>
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</tr>
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<tr>
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<td><b>
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<td>Tool use</td>
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<td>BFCL AST (avg)</td>
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<td>90.6</td>
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<td><b>91.4</b></td>
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<td>89.5</td>
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</tr>
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</tbody>
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</table>
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## Useful links
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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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tags:
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- falcon3
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base_model: tiiuae/Falcon3-7B-Base
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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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---
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# Falcon3-7B-Instruct
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**Falcon3** family of Open Foundation Models is a set of pretrained and instruct LLMs ranging from 1B to 10B.
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+
This repository contains the **Falcon3-7B-Instruct**. It achieves state of art results (at release's time) on reasoning, language understanding, instruction following, code and mathematics tasks.
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Falcon3-7B-Instruct supports 4 languages (english, french, spanish, portuguese) and a context length up to 32K.
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## Model Details
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- Uses SwiGLU and RMSNorm
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- 32K context length
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- 131K vocab size
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- Pretrained on 14 Teratokens of datasets comprising of web, code, STEM, high quality and mutlilingual data using 2048 H100 GPU chips
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- Postrained on 1.2 million samples of STEM, conversations, code, safety and function call data
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- Supports EN, FR, ES, PT
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- Developed by [Technology Innovation Institute](https://www.tii.ae)
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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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<table border="1" style="width: 100%; text-align: center; border-collapse: collapse;">
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<colgroup>
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<col style="width: 10%;">
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<col style="width: 7%;">
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<col style="width: 7%;">
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<col style="width: 7%;">
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<col style="background-color: rgba(80, 15, 213, 0.5); width: 7%;">
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</colgroup>
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<thead>
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<tr>
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<th>Category</th>
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<th>Benchmark</th>
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<th>Llama-3.2-1B</th>
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<th>Qwen2.5-1.5B</th>
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<th>SmolLM2-1.7B</th>
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<th>Falcon3-1B-Instruct</th>
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</tr>
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</thead>
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<tbody>
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<tr>
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<td rowspan="3">General</td>
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<td>MMLU (5-shot)</td>
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<td>23.4</td>
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<td><b>58.4</b></td>
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<td>48.4</td>
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<td>43.9</td>
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</tr>
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<tr>
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<td>MMLU-PRO (5-shot)</td>
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<td>11.3</td>
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<td><b>21.3</b></td>
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<td>17.2</td>
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<td>18.6</td>
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</tr>
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<tr>
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<td>IFEval</td>
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<td><b>55.8</b></td>
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<td>44.4</td>
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<td>53.0</td>
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<td>54.4</td>
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</tr>
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<tr>
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<td rowspan="3">Math</td>
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<td>GSM8K (5-shot)</td>
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<td>37.4</td>
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<td><b>57.2</b></td>
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<td>43.4</td>
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<td>38.6</td>
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</tr>
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<tr>
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<td>GSM8K (8-shot, COT)</td>
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<td>35.6</td>
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<td><b>62.2</b></td>
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<td>47.2</td>
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<td>41.8</td>
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</tr>
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<tr>
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<td>MATH Lvl-5 (4-shot)</td>
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<td><b>3.9</b></td>
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<td>0.2</td>
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<td>0.1</td>
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<td>1.0</td>
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</tr>
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<tr>
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<td rowspan="6">Reasoning</td>
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<td>Arc Challenge (25-shot)</td>
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<td>34.1</td>
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<td>47.0</td>
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<td><b>47.6</b></td>
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<td>45.9</td>
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</tr>
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<tr>
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<td>GPQA (0-shot)</td>
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<td>25.3</td>
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<td><b>29.6</b></td>
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<td>28.7</td>
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<td>26.5</td>
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</tr>
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<tr>
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<td>GPQA (0-shot, COT)</td>
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<td>13.2</td>
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<td>9.2</td>
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<td>16.0</td>
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<td><b>21.3</b></td>
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</tr>
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<tr>
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<td>MUSR (0-shot)</td>
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<td>32.4</td>
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<td>36.8</td>
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<td>33.0</td>
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<td><b>40.7</b></td>
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</tr>
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<tr>
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<td>BBH (3-shot)</td>
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<td>30.3</td>
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<td><b>38.5</b></td>
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<td>33.1</td>
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<td>35.1</td>
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</tr>
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<tr>
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<td>BBH (3-shot, COT)</td>
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<td>0.0</td>
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<td>20.3</td>
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<td>0.8</td>
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<td><b>30.5</b></td>
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</tr>
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<tr>
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<td rowspan="5">CommonSense Understanding</td>
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<td>PIQA (0-shot)</td>
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<td>72.1</td>
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<td>73.2</td>
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<td><b>74.4</b></td>
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<td>72.0</td>
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</tr>
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<tr>
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<td>SciQ (0-shot)</td>
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<td>61.8</td>
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<td>69.5</td>
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<td>71.4</td>
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<td><b>86.8</b></td>
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</tr>
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<tr>
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<td>Winogrande (0-shot)</td>
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<td>-</td>
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<td>-</td>
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<td>-</td>
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<td><b>60.2</b></td>
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</tr>
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<tr>
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<td>OpenbookQA (0-shot)</td>
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<td>40.2</td>
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<td>40.4</td>
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<td><b>42.8</b></td>
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<td>40.0</td>
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</tr>
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<tr>
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<td>MT-Bench (avg)</td>
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<td>5.4</td>
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<td><b>7.1</b></td>
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<td>6.1</td>
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<td>5.5</td>
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</tr>
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<tr>
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235 |
+
<td rowspan="1">Instructions following</td>
|
236 |
+
<td>Alapaca (WC)</td>
|
237 |
+
<td><b>8.6</b></td>
|
238 |
+
<td><b>8.6</b></td>
|
239 |
+
<td>5.4</td>
|
240 |
+
<td>6.1</td>
|
|
|
|
|
|
|
|
|
|
|
241 |
</tr>
|
242 |
</tbody>
|
243 |
</table>
|
244 |
|
|
|
|
|
|
|
|
|
245 |
## Technical Report
|
246 |
Coming soon....
|
247 |
|
tokenizer_config.json
CHANGED
@@ -16219,7 +16219,7 @@
|
|
16219 |
">>PASSWORD<<",
|
16220 |
">>KEY<<"
|
16221 |
],
|
16222 |
-
"chat_template": "{
|
16223 |
"clean_up_tokenization_spaces": true,
|
16224 |
"eos_token": "<|endoftext|>",
|
16225 |
"extra_special_tokens": {},
|
|
|
16219 |
">>PASSWORD<<",
|
16220 |
">>KEY<<"
|
16221 |
],
|
16222 |
+
"chat_template": "{% for message in messages %}{% if message['role'] == 'system' %}{{ '<|system|>\n' + message['content'] + '\n' }}{% elif message['role'] == 'user' %}{{ '<|user|>\n' + message['content'] + '\n' }}{% elif message['role'] == 'assistant' %}{% if not loop.last %}{{ '<|assistant|>\n' + message['content'] + eos_token + '\n' }}{% else %}{{ '<|assistant|>\n' + message['content'] + eos_token }}{% endif %}{% endif %}{% if loop.last and add_generation_prompt %}{{ '<|assistant|>\n' }}{% endif %}{% endfor %}",
|
16223 |
"clean_up_tokenization_spaces": true,
|
16224 |
"eos_token": "<|endoftext|>",
|
16225 |
"extra_special_tokens": {},
|