Update README.md

README.md

@@ -6,35 +6,32 @@ 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>
 
 # Falcon3-7B-Base
 
-**Falcon3** family of Open Foundation Models is a set of pretrained and instruct LLMs ranging from 1B to 10B.
+**Falcon3** family of Open Foundation Models is a set of pretrained and instruct LLMs ranging from 1B to 10B parameters.
 
-This repository contains the **Falcon3-7B-Base**. It achieves state of art results (at the time of release) on reasoning, language understanding, instruction following, code and mathematics tasks.
-Falcon3-7B-Base supports 4 languages (english, french, spanish, portuguese) and a context length up to 32K.
+This repository contains the **Falcon3-7B-Base**. It achieves state-of-the-art results (at release's time) on reasoning, language understanding, instruction following, code and mathematics tasks.
+Falcon3-7B-Base supports 4 languages (English, French, Spanish, Portuguese) and a context length of up to 32K.
 
-⚠️ **This is a raw, pretrained model, which should be further finetuned for most usecases.** 
+⚠️ **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
+  - Transformer-based causal decoder-only architecture
   - 28 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
-- Pretrained on 14 Teratokens of datasets comprising of web, code, STEM, high quality and mutlilingual data using 1024 H100 GPU chips
+  - 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
+  - 32K context length
+  - 131K vocab size
+- Pretrained on 14 Teratokens 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
@@ -65,10 +62,7 @@ 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:
 
 
 
@@ -79,7 +73,6 @@ 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>
@@ -87,7 +80,6 @@ We report in the following table our internal pipeline benchmarks.
             <th>Category</th>
             <th>Benchmark</th>
             <th>Llama3.1-8B</th>
-            <th>Qwen2-7B</th>
             <th>Qwen2.5-7B</th>
             <th>gemma-2-9b</th>
             <th>Falcon3-7B-Base</th>
@@ -98,119 +90,101 @@ We report in the following table our internal pipeline benchmarks.
             <td rowspan="3">General</td>
             <td>MMLU (5-shot)</td>
             <td>65.2</td>
-            <td>70.4</td>
-            <td>74.2</td>
-            <td>-</td>
+            <td><b>74.2</b></td>
+            <td>70.8</td>
             <td>67.5</td>
         </tr>
         <tr>
             <td>MMLU-PRO (5-shot)</td>
             <td>32.7</td>
-            <td>42.1</td>
-            <td>43.5</td>
-            <td>-</td>
+            <td><b>43.5</b></td>
+            <td>41.4</td>
             <td>39.2</td>
         </tr>
         <tr>
             <td>IFEval</td>
             <td>12.0</td>
-            <td>30.6</td>
             <td>33.9</td>
-            <td>-</td>
-            <td>34.3</td>
+            <td>21.2</td>
+            <td><b>34.3</b></td>
         </tr>
         <tr>
             <td rowspan="2">Math</td>
             <td>GSM8K (5-shot)</td>
             <td>49.4</td>
-            <td>77.9</td>
-            <td>82.9</td>
-            <td>-</td>
+            <td><b>82.9</b></td>
+            <td>69.1</td>
             <td>76.2</td>
         </tr>
         <tr>
-            <td>MATH(4-shot)</td>
+            <td>MATH Lvl-5 (4-shot)</td>
             <td>4.1</td>
-            <td>17.5</td>
             <td>15.5</td>
-            <td>-</td>
-            <td>18.0</td>
+            <td>10.5</td>
+            <td><b>18.0</b></td>
         </tr>
         <tr>
             <td rowspan="4">Reasoning</td>
             <td>Arc Challenge (25-shot)</td>
-            <td>53.4</td>
-            <td>57.4</td>
-            <td>59.0</td>
-            <td>-</td>
-            <td>59.6</td>
+            <td>58.2</td>
+            <td>63.2</td>
+            <td><b>67.5</b></td>
+            <td>63.1</td>
         </tr>
         <tr>
             <td>GPQA (0-shot)</td>
             <td>31.0</td>
-            <td>31.9</td>
             <td>33.0</td>
-            <td>-</td>
-            <td>35.5</td>
+            <td>33.4</td>
+            <td><b>35.5</b></td>
         </tr>
         <tr>
             <td>MUSR (0-shot)</td>
             <td>38.0</td>
-            <td>44.1</td>
             <td>44.2</td>
-            <td>-</td>
-            <td>47.3</td>
+            <td>45.3</td>
+            <td><b>47.3</b></td>
         </tr>
         <tr>
             <td>BBH (3-shot)</td>
             <td>46.5</td>
-            <td>53.3</td>
             <td>54.0</td>
-            <td>-</td>
+            <td><b>54.3</b></td>
             <td>51.0</td>
         </tr>
         <tr>
             <td rowspan="4">CommonSense Understanding</td>
             <td>PIQA (0-shot)</td>
-            <td>80.3</td>
-            <td>79.8</td>
-            <td>78.7</td>
-            <td>-</td>
-            <td>77.7</td>
+            <td>81.2</td>
+            <td>79.9</td>
+            <td><b>82.9</b></td>
+            <td>79.1</td>
         </tr>
         <tr>
             <td>SciQ (0-shot)</td>
-            <td>96.3</td>
-            <td>95.9</td>
-            <td>96.6</td>
-            <td>-</td>
-            <td>95.3</td>
+            <td>94.6</td>
+            <td>95.2</td>
+            <td><b>97.1</b></td>
+            <td>92.4</td>
         </tr>
         <tr>
             <td>Winogrande (0-shot)</td>
             <td>74.0</td>
-            <td>72.1</td>
             <td>72.9</td>
-            <td>-</td>
+            <td><b>74.2</b></td>
             <td>71.0</td>
         </tr>
         <tr>
             <td>OpenbookQA (0-shot)</td>
-            <td>33.4</td>
-            <td>35.2</td>
-            <td>33.6</td>
-            <td>-</td>
-            <td>31.4</td>
+            <td>44.8</td>
+            <td>47.0</td>
+            <td><b>47.2</b></td>
+            <td>43.8</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
@@ -218,7 +192,7 @@ 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},
+    title = {The Falcon 3 family of Open Models},
     author = {TII Team},
     month = {December},
     year = {2024}

generation_config.json

@@ -1,6 +1,5 @@
 {
   "_from_model_config": true,
-  "bos_token_id": 11,
   "eos_token_id": 11,
   "transformers_version": "4.46.1"
 }

special_tokens_map.json

@@ -30,5 +30,12 @@
     "normalized": false,
     "rstrip": false,
     "single_word": false
+  },
+  "pad_token": {
+    "content": "<|pad|>",
+    "lstrip": false,
+    "normalized": false,
+    "rstrip": false,
+    "single_word": false
   }
 }

tokenizer.json

@@ -18212,7 +18212,7 @@
     },
     {
       "id": 2023,
-      "content": ">>UNUSED_1897<<",
+      "content": "<|pad|>",
       "single_word": false,
       "lstrip": false,
       "rstrip": false,
@@ -20280,7 +20280,7 @@
       ">>UNUSED_1894<<": 2020,
       ">>UNUSED_1895<<": 2021,
       ">>UNUSED_1896<<": 2022,
-      ">>UNUSED_1897<<": 2023,
+      "<|pad|>": 2023,
       "!": 2024,
       "\"": 2025,
       "#": 2026,

tokenizer_config.json

@@ -16186,7 +16186,7 @@
       "special": true
     },
     "2023": {
-      "content": ">>UNUSED_1897<<",
+      "content": "<|pad|>",
       "lstrip": false,
       "normalized": false,
       "rstrip": false,
@@ -16221,6 +16221,12 @@
   ],
   "clean_up_tokenization_spaces": true,
   "eos_token": "<|endoftext|>",
+  "extra_special_tokens": {},
+  "model_input_names": [
+    "input_ids",
+    "attention_mask"
+  ],
   "model_max_length": 32768,
+  "pad_token": "<|pad|>",
   "tokenizer_class": "PreTrainedTokenizerFast"
 }