push model card

README.md

@@ -6,22 +6,18 @@ language:
 - pt
 tags:
 - falcon3
-license: other
-license_name: falcon-llm-license
+license: other 
+license_name: falcon-llm-license 
 license_link: https://falconllm.tii.ae/falcon-terms-and-conditions.html
-library_name: transformers
 ---
 
-<div align="center">
-    <img src="https://huggingface.co/datasets/tiiuae/documentation-images/resolve/main/general/falco3-logo.png" alt="drawing" width="500"/>
-</div>
 
 # Falcon3-1B-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 **Falcon3-1B-Base**. It achieves strong results on reasoning, language understanding, instruction following, code and mathematics tasks.
-Falcon3-1B-Base supports 4 languages (English, French, Spanish, Portuguese) and a context length of up to 4K.
+Falcon3-1B-Base supports 4 languages (English, French, Spanish, Portuguese) and a context length of up to 32K.
 It was pruned in terms of depth, width, number of heads, and embedding channels from a larger 3B Falcon model, and was efficiently trained on only 80 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.** 
@@ -29,14 +25,14 @@ It was pruned in terms of depth, width, number of heads, and embedding channels
 ## Model Details
 - Architecture
   - Transformer-based causal decoder-only architecture
-  - 18 decoder blocks
+  - 22 decoder blocks
   - Grouped Query Attention (GQA) for faster inference: 8 query heads and 4 key-value heads
   - Wider head dimension: 256
   - High RoPE value to support long context understanding: 1000042
   - Uses SwiGLU and RMSNorm
-  - 4K context length
+  - 32K context length
   - 131K vocab size
-- Pruned and healed using larger Falcon models (3B and 7B respectively) on only 80 Gigatokens of datasets comprising of web, code, STEM, high quality and multilingual data using 256 H100 GPU chips
+- Pruned and healed using larger Falcon models (3B and 7B respectively) on only 80 Gigatokens of datasets comprising of web, code, STEM, high quality and mutlilingual data using 256 H100 GPU chips
 - Supports EN, FR, ES, PT
 - Developed by [Technology Innovation Institute](https://www.tii.ae)
 - License: TII Falcon-LLM License 2.0
@@ -67,10 +63,7 @@ print(response[0]['generated_text'])
 <br>
 
 ## Benchmarks
-We report in the following table our internal pipeline benchmarks.
- - We use [lm-evaluation harness](https://github.com/EleutherAI/lm-evaluation-harness).
- - We report **raw scores**.
- - We use same batch-size across all models.
+We report in the following table our internal pipeline benchmarks:
 
 
 
@@ -81,6 +74,7 @@ We report in the following table our internal pipeline benchmarks.
         <col style="width: 7%;">
         <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>
@@ -98,21 +92,21 @@ We report in the following table our internal pipeline benchmarks.
             <td rowspan="3">General</td>
             <td>MMLU (5-shot)</td>
             <td>31.1</td>
-            <td><b>61.0</b></td>
+            <td>61.0</td>
             <td>50.1</td>
             <td>42.5</td>
         </tr>
         <tr>
             <td>MMLU-PRO (5-shot)</td>
             <td>11.7</td>
-            <td><b>28.4</b></td>
+            <td>28.4</td>
             <td>21.3</td>
             <td>16.1</td>
         </tr>
         <tr>
             <td>IFEval</td>
             <td>14.8</td>
-            <td><b>26.0</b></td>
+            <td>26.0</td>
             <td>24.2</td>
             <td>25.2</td>
         </tr>
@@ -120,14 +114,14 @@ We report in the following table our internal pipeline benchmarks.
             <td rowspan="2">Math</td>
             <td>GSM8K (5-shot)</td>
             <td>6.6</td>
-            <td><b>62.2</b></td>
+            <td>62.2</td>
             <td>31.0</td>
             <td>34.3</td>
         </tr>
         <tr>
             <td>MATH Lvl-5 (4-shot)</td>
             <td>0.2</td>
-            <td><b>6.7</b></td>
+            <td>6.7</td>
             <td>1.4</td>
             <td>2.2</td>
         </tr>
@@ -135,7 +129,7 @@ We report in the following table our internal pipeline benchmarks.
             <td rowspan="4">Reasoning</td>
             <td>Arc Challenge (25-shot)</td>
             <td>40.2</td>
-            <td><b>54.8</b></td>
+            <td>54.8</td>
             <td>54.1</td>
             <td>48.1</td>
         </tr>
@@ -143,7 +137,7 @@ We report in the following table our internal pipeline benchmarks.
             <td>GPQA (0-shot)</td>
             <td>24.2</td>
             <td>28.1</td>
-            <td><b>28.9</b></td>
+            <td>28.9</td>
             <td>28.1</td>
         </tr>
         <tr>
@@ -151,12 +145,12 @@ We report in the following table our internal pipeline benchmarks.
             <td>34.5</td>
             <td>35.5</td>
             <td>34.7</td>
-            <td><b>41.9</b></td>
+            <td>41.9</td>
         </tr>
         <tr>
             <td>BBH (3-shot)</td>
             <td>31.2</td>
-            <td><b>41.1</b></td>
+            <td>41.1</td>
             <td>34.2</td>
             <td>36.0</td>
         </tr>
@@ -165,13 +159,13 @@ We report in the following table our internal pipeline benchmarks.
             <td>PIQA (0-shot)</td>
             <td>74.5</td>
             <td>76.0</td>
-            <td><b>77.5</b></td>
+            <td>77.5</td>
             <td>74.5</td>
         </tr>
         <tr>
             <td>SciQ (0-shot)</td>
             <td>88.5</td>
-            <td><b>93.1</b></td>
+            <td>93.1</td>
             <td>90.8</td>
             <td>91.1</td>
         </tr>
@@ -179,34 +173,29 @@ We report in the following table our internal pipeline benchmarks.
             <td>Winogrande (0-shot)</td>
             <td>60.4</td>
             <td>63.0</td>
-            <td><b>66.1</b></td>
+            <td>66.1</td>
             <td>61.2</td>
         </tr>
         <tr>
             <td>OpenbookQA (0-shot)</td>
             <td>37.4</td>
             <td>40.4</td>
-            <td><b>44.0</b></td>
+            <td>44.0</td>
             <td>41.0</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.
- 
+If Falcon3 family 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},
+    title = {The Falcon 3 family of Open Models},
+    author = {TII Team},
     month = {December},
     year = {2024}
 }

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