falcon3 release

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README.md

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+---
+language:
+- en
+- fr
+- es
+- pt
+tags:
+- falcon3
+license: other 
+license_name: falcon-llm-license 
+license_link: https://falconllm.tii.ae/falcon-terms-and-conditions.html
+---
+
+<div align="center">
+    <img src="https://huggingface.co/datasets/tiiuae/documentation-images/resolve/main/general/falco3-logo.png" alt="drawing" width="500"/>
+</div>
+
+# Falcon3-3B-Base
+
+**Falcon3** family of Open Foundation Models is a set of pretrained and instruct LLMs ranging from 1B to 10B parameters.
+
+This repository contains the **Falcon3-3B-Base**. It achieves strong results on reasoning, language understanding, instruction following, code and mathematics tasks.
+Falcon3-3B-Base supports 4 languages (English, French, Spanish, Portuguese) and a context length of up to 8K.
+It was pruned in terms of depth and width from Falcon3-7B-Base and was efficiently trained on only 100 GT using a knowledge distillation objective.
+
+⚠️ **This is a raw, pretrained model, which should be further finetuned using SFT, RLHF, continued pretraining, etc. for most use cases.** 
+
+## Model Details
+- Architecture
+  - Transformer-based causal decoder-only architecture
+  - 22 decoder blocks
+  - Grouped Query Attention (GQA) for faster inference: 12 query heads and 4 key-value heads
+  - Wider head dimension: 256
+  - High RoPE value to support long context understanding: 1000042
+  - Uses SwiGLU and RMSNorm
+  - 8K context length
+  - 131K vocab size
+- Pruned and healed from Falcon3-7B-Base on only 100 Gigatokens of datasets comprising of web, code, STEM, high quality and mutlilingual data using 1024 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/Falcon3-3B-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>Llama3.2-3B</th>
+            <th>Qwen2.5-3B</th>
+            <th>Minitron-4B</th>
+            <th>Falcon3-3B-Base</th>
+        </tr>
+    </thead>
+    <tbody>
+        <tr>
+            <td rowspan="3">General</td>
+            <td>MMLU (5-shot)</td>
+            <td>56.1</td>
+            <td><b>65.6</b></td>
+            <td>58.7</td>
+            <td>55.5</td>
+        </tr>
+        <tr>
+            <td>MMLU-PRO (5-shot)</td>
+            <td>24.9</td>
+            <td><b>32</b></td>
+            <td>26.2</td>
+            <td>28.8</td>
+        </tr>
+        <tr>
+            <td>IFEval</td>
+            <td>12.8</td>
+            <td>27</td>
+            <td>22.8</td>
+            <td><b>27.7</b></td>
+        </tr>
+        <tr>
+            <td rowspan="2">Math</td>
+            <td>GSM8K (5-shot)</td>
+            <td>26.7</td>
+            <td><b>69</b></td>
+            <td>25.7</td>
+            <td>63.9</td>
+        </tr>
+        <tr>
+            <td>MATH Lvl-5 (4-shot)</td>
+            <td>1.4</td>
+            <td>8.4</td>
+            <td>1.7</td>
+            <td><b>9.4</b></td>
+        </tr>
+        <tr>
+            <td rowspan="4">Reasoning</td>
+            <td>Arc Challenge (25-shot)</td>
+            <td>50.8</td>
+            <td><b>55.5</b></td>
+            <td>50.3</td>
+            <td>54.9</td>
+        </tr>
+        <tr>
+            <td>GPQA (0-shot)</td>
+            <td>27.5</td>
+            <td>27.5</td>
+            <td><b>38.6</b></td>
+            <td>31.2</td>
+        </tr>
+        <tr>
+            <td>MUSR (0-shot)</td>
+            <td>35.2</td>
+            <td><b>43</b></td>
+            <td>42.1</td>
+            <td>37.5</td>
+        </tr>
+        <tr>
+            <td>BBH (3-shot)</td>
+            <td>38.6</td>
+            <td><b>46.1</b></td>
+            <td>40.9</td>
+            <td>44.2</td>
+        </tr>
+        <tr>
+            <td rowspan="4">CommonSense Understanding</td>
+            <td>PIQA (0-shot)</td>
+            <td>77.4</td>
+            <td><b>78.9</b></td>
+            <td>78.3</td>
+            <td>75.6</td>
+        </tr>
+        <tr>
+            <td>SciQ (0-shot)</td>
+            <td>92.7</td>
+            <td>95.6</td>
+            <td><b>96.1</b></td>
+            <td>93.1</td>
+        </tr>
+        <tr>
+            <td>Winogrande (0-shot)</td>
+            <td><b>69.7</b></td>
+            <td>68.8</td>
+            <td>68.4</td>
+            <td>64.6</td>
+        </tr>
+        <tr>
+            <td>OpenbookQA (0-shot)</td>
+            <td><b>43.2</b></td>
+            <td>42.2</td>
+            <td>43</td>
+            <td>39.4</td>
+        </tr>
+    </tbody>
+</table>
+
+## Useful links
+- View our [release blogpost](https://huggingface.co/blog/falcon3).
+- Feel free to join [our discord server](https://discord.gg/fwXpMyGc) if you have any questions or to interact with our researchers and developers.
+
+## Technical Report
+Coming soon....
+
+## Citation
+If the Falcon3 family of models were helpful to your work, feel free to give us a cite.
+ 
+```
+@misc{Falcon3,
+    title = {The Falcon 3 Family of Open Models},
+    url = {https://huggingface.co/blog/falcon3},
+    author = {Falcon-LLM Team},
+    month = {December},
+    year = {2024}
+}
+```

config.json

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+{
+  "architectures": [
+    "LlamaForCausalLM"
+  ],
+  "activation": "swiglu",
+  "attention_bias": false,
+  "attention_dropout": 0.0,
+  "eos_token_id": 11,
+  "head_dim": 256,
+  "hidden_act": "silu",
+  "hidden_size": 3072,
+  "intermediate_size": 9216,
+  "max_position_embeddings": 32768,
+  "mlp_bias": false,
+  "model_type": "llama",
+  "num_attention_heads": 12,
+  "num_hidden_layers": 22,
+  "num_key_value_heads": 4,
+  "pretraining_tp": 1,
+  "rms_norm_eps": 1e-06,
+  "rope_scaling": null,
+  "rope_theta": 1000042,
+  "tie_word_embeddings": false,
+  "torch_dtype": "bfloat16",
+  "transformers_version": "4.46.1",
+  "use_cache": true,
+  "vocab_size": 131072
+}

generation_config.json

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+  "_from_model_config": true,
+  "eos_token_id": 11,
+  "transformers_version": "4.46.1"
+}

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special_tokens_map.json

@@ -0,0 +1,41 @@
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+    "rstrip": false,
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+    "normalized": false,
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+    "single_word": false
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+}