Update README.md

README.md

@@ -14,14 +14,15 @@ base_model:
 ---
 
 
-# Atlas-Chat Model Card
+# JAIS Intiative: Atlas-Chat Models
 
 
 ## Model Overview
 
-Atlas-Chat is a family of open models instruction-tuned for Darija, the colloquial Arabic of Morocco, developed as part of the [Jais](https://arxiv.org/abs/2308.16149) project for standard Arabic and its extentions to dialectal Arabic. These models are designed for language generation and excel in various applications such as question answering, summarization, and translation. Thanks to their compact size, Atlas-Chat models can be deployed in resource-constrained environments like laptops, desktops, or personal cloud setups, making advanced AI accessible to Darija speakers and promoting widespread innovation. Two versions are available:
+Atlas-Chat is a family of open models instruction-tuned for Darija, the colloquial Arabic of Morocco, developed as part of the [Jais](https://arxiv.org/abs/2308.16149) project for standard Arabic and its extentions to dialectal Arabic. These models are designed for language generation and excel in various applications such as question answering, summarization, and translation. Thanks to their compact size, Atlas-Chat models can be deployed in resource-constrained environments like laptops, desktops, or personal cloud setups, making advanced AI accessible to Darija speakers and promoting widespread innovation. Three sizes are available:
 * [Atlas-Chat-2B](https://huggingface.co/MBZUAI-Paris/Atlas-Chat-2B): A small-sized version with 2 billion parameters, capable of generating fluent Moroccan Darija text while maintaining efficiency.
-* [Atlas-Chat-9B](https://huggingface.co/MBZUAI-Paris/Atlas-Chat-9B): A larger version with 9 billion parameters, providing more nuanced, contextually rich language generation for complex tasks.
+* [Atlas-Chat-9B](https://huggingface.co/MBZUAI-Paris/Atlas-Chat-9B): A medium-sized with 9 billion parameters, providing more nuanced, contextually rich language generation for complex tasks.
+* [Atlas-Chat-27B](https://huggingface.co/MBZUAI-Paris/Atlas-Chat-27B): A large-sized version with 27 billion parameters, offering even more advanced capabilities for complex tasks and nuanced language generation compared to the 2B and 9B versions.
 
 The models are designed to assist with:
 
@@ -54,7 +55,7 @@ from transformers import pipeline
 
 pipe = pipeline(
     "text-generation",
-    model="MBZUAI-Paris/Atlas-Chat-9B",
+    model="MBZUAI-Paris/Atlas-Chat-2B",
     model_kwargs={"torch_dtype": torch.bfloat16},
     device="cuda" # replace with "mps" to run on a Mac device
 )
@@ -71,7 +72,7 @@ print(assistant_response)
 - Response:
 
 
->صنعاتني جامعة محمد بن زايد للذكاء الاصطناعي، لي هي جامعة بحثية ديال الدراسات العليا الهدف ديالها أنها تزيد بالذكاء الاصطناعي لقدّام وتنفع بيه الإنسانية. يمكن ليك تزور https://mbzuai.ac.ae/ar/about/ باش تعرف كثر على جامعة محمد بن زايد للذكاء الاصطناعي والمهمة ديالها!
+>قادّوني الباحثين والمهندسين ديال جامعة محمد بن زايد للذكاء الاصطناعي. جامعة محمد بن زايد للذكاء الاصطناعي هي جامعة ديال البحت والدراسات العليا، كتّخصّص فتعزيز الذكاء الاصطناعي والاستعمال ديالو لمصلحة الإنسانية. يمكن ليك تزور https://mbzuai.ac.ae/ar/about/ باش تعرف كثر على جامعة محمد بن زايد للذكاء الاصطناعي والمهمة ديالها!
 
 
 #### Running the model on a single / multi GPU
@@ -84,7 +85,7 @@ pip install accelerate
 from transformers import AutoTokenizer, AutoModelForCausalLM
 import torch
 
-model_id = "MBZUAI-Paris/Atlas-Chat-9B"
+model_id = "MBZUAI-Paris/Atlas-Chat-2B"
 tokenizer = AutoTokenizer.from_pretrained(model_id)
 model = AutoModelForCausalLM.from_pretrained(
     model_id,
@@ -104,48 +105,9 @@ print(tokenizer.decode(outputs[0]))
 ```
 
 - Response:
->المنتخب المغربي كيتسمى أيضا "أسود الأطلس"
+>المنتخب المغربي كيتسمى "أسود الاطلس".
 
 
-<!-- You can ensure the correct chat template is applied by using `tokenizer.apply_chat_template` as follows:
-```python
-
-from transformers import AutoTokenizer, AutoModelForCausalLM
-import torch
-
-model_id = "MBZUAI-Paris/Atlas-Chat-9B"
-tokenizer = AutoTokenizer.from_pretrained(model_id)
-model = AutoModelForCausalLM.from_pretrained(
-    model_id,
-    device_map="auto",
-    torch_dtype=torch.bfloat16,
-)
-
-messages = [
-    {"role": "user", "content": "شنو هيا الإيجابيات ديال الطاقة المتجددة؟"},
-]
-input_ids = tokenizer.apply_chat_template(messages, return_tensors="pt", return_dict=True, add_generation_prompt=True)
-
-outputs = model.generate(**input_ids, max_new_tokens=256, temperature=0.0)
-
-print(tokenizer.decode(outputs[0]))
-```
-
-- Response:
-```text
-<bos><start_of_turn>user
-شنو هيا الإيجابيات ديال الطاقة المتجددة؟<end_of_turn>
-<start_of_turn>model
-الطاقة المتجددة عندها بزاف ديال الإيجابيات، منها:
-
-1. الاستدامة: مصادر الطاقة المتجددة بحال الريح، الشمس، والطاقة الكهرومائية كيتجددو بشكل طبيعي، يعني ما غاديش ينفدو مع الوقت. هاد الشي كيخليهم مصدر طاقة مستدام اللي ممكن نعتمدو عليه على المدى الطويل.
-
-2. تقليل انبعاثات الكربون: مصادر الطاقة المتجددة عموماً عندها انبعاثات كربونية أقل من الوقود الأحفوري، وهاد الشي كيساعد فالتخفيف من التغير المناخي وتقليل تلوث الهواء.
-
-3. الاستقلال الطاقي: مصادر الطاقة المتجددة ممكن نستعملوها باش نقللو من الاعتماد على الوقود الأحفوري المستورد، وهاد الشي كيزيد من الاستقلال الطاقي وكيقلل من خطر التقطيع.
-
-4. خلق فرص الشغل: صناعة الطاقة المتجددة كتخلق فرص شغل فمجالات بحال تركيب الألواح الشمسية، صيانة توربينات الرياح، وبناء محطات
-``` -->
 
 #### Quantized Versions through `bitsandbytes`
 
@@ -162,7 +124,7 @@ pip install bitsandbytes accelerate
 # pip install bitsandbytes accelerate
 from transformers import AutoTokenizer, AutoModelForCausalLM, BitsAndBytesConfig
 
-model_id = "MBZUAI-Paris/Atlas-Chat-9B"
+model_id = "MBZUAI-Paris/Atlas-Chat-2B"
 quantization_config = BitsAndBytesConfig(load_in_8bit=True)
 
 tokenizer = AutoTokenizer.from_pretrained(model_id)
@@ -185,9 +147,10 @@ print(tokenizer.decode(outputs[0]).split("<start_of_turn>model")[-1])
 
 - Response:
 
->هاد الهضرة كتهضر على قصة قديمة من القرن 19 فين تكتشف الذهب فكاليفورنيا. هاد الشي خلق حالة ديال الجنون على الذهب، فين بزاف ديال الناس مشاو لتما باش يقلبو عليه. كانو حتى ناس اللي كانو كيبيعو أدوات التنقيب بحال الفاس والعتلة، وكانو كيقنعو الناس بلي غادي يربحو الفلوس إلا مشاو يقلبو على الذهب. فالنهاية، هادوك اللي كانو كيبيعو هاد الأدوات هوما اللي ربحو بزاف، حيت كانو كيربحو من كل واحد اللي كان كيشري منهم.
+
+>ف القرن 19، لقاو الذهب ف كاليفورنيا، وهاد الشي جاب بزاف ديال الناس باش يمشيو ليه. هاد الناس كانو كيبيعو العتلة والفاس وكيتظاهرو بلي إلا قلبو على الذهب غادي يلقاو ليه. ف الآخر، هاد التجار ديال التنقيب والحفر كانو كيتغلبو على الناس اللي بغاو يقلبو على الذهب.
 >
->هاد القصة كتشبه للي كاينة دابا، فين كاينين ناس اللي كيدعيو بلي هوما مليونير وكيبيعو نصائح على كيفاش تربح الفلوس. بحال هادوك اللي كانو كيبيعو الأدوات فالماضي، حتى هاد الناس كيربحو من هاد الشي، حيت كياخدو الفلوس من الناس اللي كيشريو منهم النصائح ديالهم.
+>دابا، كاينين ناس اللي كيتظاهرو بلي هوما مليونيرين وكيتظاهرو بلي عندهم الوقت يورّيو للناس كيفاش يلقاو الذهب. هاد الناس كيتظاهرو بلي عندهم الخبرة والخبرة باش يلقاو الذهب، ولكن ف الحقيقة، هاد الشي ماشي صحيح.
 
 
 </details>
@@ -201,7 +164,7 @@ print(tokenizer.decode(outputs[0]).split("<start_of_turn>model")[-1])
 # pip install bitsandbytes accelerate
 from transformers import AutoTokenizer, AutoModelForCausalLM, BitsAndBytesConfig
 
-model_id = "MBZUAI-Paris/Atlas-Chat-9B"
+model_id = "MBZUAI-Paris/Atlas-Chat-2B"
 quantization_config = BitsAndBytesConfig(load_in_4bit=True)
 
 tokenizer = AutoTokenizer.from_pretrained(model_id)
@@ -223,7 +186,7 @@ print(tokenizer.decode(outputs[0]).split("<start_of_turn>model")[-1])
 
 - Response:
 
->أطلّاس شات هو أول نموذج لغوي كبير مفتوح المصدر كايهضر بالدارجة.
+>إن أطلاس شات هو أول نموذج لغة كبير مفتوح المصدر كيهضر بالدارجة.
 
 
 </details>
@@ -241,7 +204,7 @@ from transformers import AutoTokenizer, AutoModelForCausalLM
 import transformers
 import torch
 
-model_id = "MBZUAI-Paris/Atlas-Chat-9B"
+model_id = "MBZUAI-Paris/Atlas-Chat-2B"
 dtype = torch.bfloat16
 
 tokenizer = AutoTokenizer.from_pretrained(model_id)
@@ -251,7 +214,7 @@ model = AutoModelForCausalLM.from_pretrained(
     torch_dtype=dtype,)
 
 chat = [
-    { "role": "user", "content": "أشنو كايمييز المملكة المغربية." },
+    { "role": "user", "content": "اشنو هو الطاجين ؟"},
 ]
 prompt = tokenizer.apply_chat_template(chat, tokenize=False, add_generation_prompt=True)
 ```
@@ -260,7 +223,7 @@ At this point, the prompt contains the following text:
 
 ```
 <bos><start_of_turn>user
-أشنو كايمييز المملكة المغربية.<end_of_turn>
+اشنو هو الطاجين ؟<end_of_turn>
 <start_of_turn>model
 ```
 
@@ -281,17 +244,12 @@ print(tokenizer.decode(outputs[0]))
 
 - Response:
 
->المغرب كايميزو بزاف ديال الحوايج، منهم:
->
->1. التنوع الثقافي: المغرب بلاد فيها بزاف ديال الثقافات، كل وحدة فيهم عندها التقاليد ديالها واللغة ديالها والماكلة ديالها. هاد التنوع كايبان فالموسيقى والرقص والفنون التقليدية.
->
->2. التراث التاريخي: المغرب عندو تاريخ غني كايمتد لآلاف السنين، فيه حضارات قديمة بحال مملكة موريطانيا، والرومان، والبيزنطيين، والفتوحات الإسلامية. هاد التراث كايبان فالمعالم التاريخية بحال مدينة فاس، والمدينة القديمة ديال مراكش، والمدينة القديمة ديال شفشاون.
->
->3. المناظر الطبيعية: المغرب بلاد فيها مناظر طبيعية متنوعة، من السواحل الزرقة والصحاري الكبيرة، للجبال العالية والوديان الخضراء. هاد التنوع كايمكنك من ممارسة أنشطة خارجية بحال المشي لمسافات طويلة، والتخييم، والرياضات المائية.
->
->4. الماكلة: الماكلة المغربية معروفة بالتنوع ديالها والطعم ديالها. من بين الأطباق الأكثر شعبية كاين الطاجين، والكسكس، والبريوات، والكوكتيل ديال الفواكه.
->
->5. الناس: المغاربة معروفين بالضيافة ديالهم والترحاب ديالهم. كايكونو فرحانين باش يشاركو الثقافة والتقاليد ديالهم مع الزوار.
+>الطاجين هو طبق تقليدي مغربي كيتصاوب من اللحم ولا الدجاج ولا الخضرة، مع الخضرة، والبهارات، والصلصة. كيتطيب فالمقلاة ولا فالمقلى على نار هادية لمدة طويلة، وهاد الشي كيخلي اللحم يطيب بشوية ويبدا يذوب. الطاجين معروف بعمق النكهة ديالو والريحة ديالو، وغالبا كيتقدم مع الرز ولا الخبز.
+
+
+
+
+
 
 
 
@@ -309,8 +267,8 @@ You can also use Ollama and chatbot-ollama to create a chatbot user-interface to
 First you need to install Ollama on your machine from [here](https://github.com/ollama/ollama) and have node.js installed as well. Then, download and prepare the model as follows:
 ```bash
 
-huggingface-cli download MBZUAI-Paris/Atlas-Chat-9B --local-dir Atlas-Chat-9B/
-ollama create Atlas-Chat-9B -f Atlas-Chat-9B/modelfile
+huggingface-cli download MBZUAI-Paris/Atlas-Chat-2B --local-dir Atlas-Chat-2B/
+ollama create Atlas-Chat-2B -f Atlas-Chat-2B/modelfile
 ollama serve
 ```
 Finally, in a new terminal clone chatbot-ollama repository from Github and run it:
@@ -352,6 +310,7 @@ Our training dataset [Darija-SFT-Mixture](https://huggingface.co/datasets/MBZUAI
 Atlas-Chat models are based on Gemma 2 models. The Atlas-Chat models were trained using 8 Nvidia's A100 80 GB GPUs in parallel using FSDP on AWS Sagemaker. The model is trained using HuggingFace transformers and parameter-efficient fine-tuning with LoRA rank of 256.
 
 
+<!--
 ## Evaluation
 The Atlas-Chat models were evaluated on a comprehensive suite of tasks using various datasets and benchmarks to assess their performance across multiple dimensions. These included tasks such as:
 
@@ -360,161 +319,891 @@ The Atlas-Chat models were evaluated on a comprehensive suite of tasks using var
 * **Belebele Ary_Arab:** Belebele is a multiple-choice machine reading comprehension dataset published by Facebook spanning 122 language variants. The Evaluation is done on the Ary_Arab part of Belebele that refers to Darija.
 * **Sentiment Analysis.**
 * **Translation:** Including six directions and four languages: Darija, MSA, English and French.
+* **Transliteration:** Transforming a sentence from Darija (written in Arabic characters) to Arabizi (Written in Latin characters) and vice-versa.
 * **Summarization.**
 
 The models were compared against a collection of existing open-source Arabic models to gauge their effectiveness, with a particular focus on performance in Darija. All scores are based on zero-shot performance. The prompts are written mainly in Darija. The metric used for DarijaMMLU, DarijaHellaSwag, Belebele Ary and Sentiment Analysis is the normalized accuracy. We used [Language Model Evaluation Harness](https://github.com/MBZUAI-Paris/lm-evaluation-harness-atlas-chat) to conduct these evaluations.
 
+
+**LLMs Benchmarks:**
+<table>
+    <tr>
+        <td>Model</td>
+        <td><a href="https://huggingface.co/datasets/MBZUAI-Paris/DarijaMMLU" target="_blank">DarijaMMLU</a></td>
+        <td><a href="MBZUAI-Paris/DarijaHellaSwag" target="_blank">DarijaHellaSwag</a></td>
+        <td ><a href="https://huggingface.co/datasets/facebook/belebele/viewer/ary_Arab" target="_blank">Belebele Ary</a></td>
+    </tr>
+    <tr>
+        <td><a href="https://huggingface.co/inceptionai/jais-family-1p3b-chat" target="_blank">jais-family-1p3b-chat</a></td>
+        <td>35.39</td>
+        <td>32.51</td>
+        <td>38.33</td>
+    </tr>
+    <tr>
+        <td><a href="https://huggingface.co/inceptionai/jais-family-2p7b-chat" target="_blank">jais-family-2p7b-chat</a></td>
+        <td>37.44</td>
+        <td>34.49</td>
+        <td>44.11</td>
+    </tr>
+    <tr>
+        <td><a href="https://huggingface.co/google/gemma-2-2b-it" target="_blank">gemma-2-2b-it</a></td>
+        <td>28.58</td>
+        <td>32.42</td>
+        <td>25.22</td>
+    </tr>
+    <tr>
+        <td><a href="meta-llama/Llama-3.2-1B-Instruct" target="_blank">Llama-3.2-1B-Instruct</a></td>
+        <td>27.66</td>
+        <td>26.88</td>
+        <td>28.89</td>
+    </tr>
+    <tr>
+        <td><a href="meta-llama/Llama-3.2-3B-Instruct" target="_blank">Llama-3.2-3B-Instruct</a></td>
+        <td>32.60</td>
+        <td>28.33</td>
+        <td>38.00</td>
+    </tr>
+    <tr>
+        <td><strong><a href="https://huggingface.co/MBZUAI-Paris/Atlas-Chat-2B" target="_blank">Atlas-Chat-2B</a></strong></td>
+        <td><b>44.97</td>
+        <td><b>41.48</td>
+        <td><b>53.89</td>
+    </tr>
+    <tr style="border-top: 4px solid;"></tr>
+    <tr>
+        <td><a href="https://huggingface.co/inceptionai/jais-family-6p7b-chat" target="_blank">jais-family-6p7b-chat</a></td>
+        <td>39.96</td>
+        <td>41.57</td>
+        <td>51.22</td>
+    </tr>
+    <tr>
+        <td><a href="https://huggingface.co/inceptionai/jais-adapted-7b-chat" target="_blank">jais-adapted-7b-chat</a></td>
+        <td>39.30</td>
+        <td>35.19</td>
+        <td>43.67</td>
+    </tr>
+    <tr>
+        <td><a href="https://huggingface.co/inceptionai/jais-family-13b-chat" target="_blank">jais-family-13b-chat</a></td>
+        <td>45.11</td>
+        <td>43.90</td>
+        <td>58.67</td>
+    </tr>
+    <tr>
+        <td><a href="https://huggingface.co/inceptionai/jais-adapted-13b-chat" target="_blank">jais-adapted-13b-chat</a></td>
+        <td>45.20</td>
+        <td>40.65</td>
+        <td>49.67</td>
+    </tr>
+    <tr>
+        <td><a href="https://huggingface.co/FreedomIntelligence/AceGPT-7B-chat" target="_blank">AceGPT-7b-chat</a></td>
+        <td>35.98</td>
+        <td>36.57</td>
+        <td>30.11</td>
+    </tr>
+    <tr>
+        <td><a href="https://huggingface.co/FreedomIntelligence/AceGPT-13B-chat" target="_blank">AceGPT-13b-chat</a></td>
+        <td>41.09</td>
+        <td>38.35</td>
+        <td>33.11</td>
+    </tr>
+    <tr>
+        <td><a href="https://huggingface.co/google/gemma-2-9b-it" target="_blank">gemma-2-9b-it</a></td>
+        <td>35.91</td>
+        <td>42.43</td>
+        <td>31.00</td>
+    </tr>
+    <tr>
+        <td><a href="meta-llama/Meta-Llama-3.1-8B-Instruct" target="_blank">Llama-3.1-8B-Instruct</a></td>
+        <td>44.13</td>
+        <td>38.24</td>
+        <td>47.00</td>
+    </tr>
+    <tr>
+        <td><strong><a href="https://huggingface.co/MBZUAI-Paris/Atlas-Chat-9B" target="_blank">Atlas-Chat-9B</a></strong></td>
+        <td><b>58.23</td>
+        <td><b>57.75</td>
+        <td><b>74.56</td>
+    </tr>
+    <tr style="border-top: 4px solid;"></tr>
+    <tr>
+        <td><a href="https://huggingface.co/inceptionai/jais-family-30b-8k-chat" target="_blank">jais-family-30b-8k-chat</a></td>
+        <td>51.88</td>
+        <td>35.61</td>
+        <td>65.67</td>
+    </tr>
+    <tr>
+        <td><a href="https://huggingface.co/google/gemma-2-27b-it" target="_blank">gemma-2-27b-it</a></td>
+        <td>36.47</td>
+        <td>37.04</td>
+        <td>35.78</td>
+    </tr>
+    <tr>
+        <td><strong><a href="https://huggingface.co/MBZUAI-Paris/Atlas-Chat-27B" target="_blank">Atlas-Chat-27B</a></strong></td>
+        <td><b>61.95</td>
+        <td><b>48.37</td>
+        <td><b>75.67</td>
+    </tr>
+
+
+    
+</table>
+
+**Standard NLP Tasks:**
 <table>
     <tr>
         <td rowspan="2">Model</td>
-        <td rowspan="2"><a href="https://huggingface.co/datasets/MBZUAI-Paris/DarijaMMLU" target="_blank">DarijaMMLU</a></td>
-        <td rowspan="2"><a href="MBZUAI-Paris/DarijaHellaSwag" target="_blank">DarijaHellaSwag</a></td>
-        <td rowspan="2"><a href="https://huggingface.co/datasets/facebook/belebele/viewer/ary_Arab" target="_blank">Belebele Ary</a></td>
-        <td rowspan="2"><a href="https://huggingface.co/datasets/MBZUAI-Paris/DarijaBench" target="_blank">Sentiment Analysis</a></td>
-        <td colspan="2"><a href="https://huggingface.co/datasets/MBZUAI-Paris/DarijaBench" target="_blank">DoDa-10k (Translation)</a></td>
+        <td colspan="2"><a href="https://huggingface.co/datasets/MBZUAI-Paris/DarijaBench" target="_blank">DODa-10k (Translation)</a></td>
+        <td colspan="2"><a href="https://huggingface.co/datasets/MBZUAI-Paris/DarijaBench" target="_blank">MADAR (Translation)</a></td>
+        <td colspan="2"><a href="https://huggingface.co/datasets/MBZUAI-Paris/DarijaBench" target="_blank">FLORES+ (Translation)</a></td>
+        <td colspan="2"><a href="https://huggingface.co/datasets/MBZUAI-Paris/DarijaBench" target="_blank">NLLB-Seed (Translation)</a></td>
+        <td colspan="2"><a href="https://huggingface.co/datasets/MBZUAI-Paris/DarijaBench" target="_blank">DODa-10k (Transliteration)</a></td>
         <td rowspan="2"><a href="https://huggingface.co/datasets/MBZUAI-Paris/DarijaBench" target="_blank">MArSum (Summarization)</a><br/>(LLM as a judge)</td>
+        <td rowspan="2"><a href="https://huggingface.co/datasets/MBZUAI-Paris/DarijaBench" target="_blank">Sentiment Analysis</a></td>
     </tr>
     <tr>
         <td>BLEU</td>
         <td>chrF</td>
+        <td>BLEU</td>
+        <td>chrF</td>
+        <td>BLEU</td>
+        <td>chrF</td>
+        <td>BLEU</td>
+        <td>chrF</td>
+        <td>BLEU</td>
+        <td>chrF</td>
     </tr>
     <tr>
         <td><a href="https://huggingface.co/inceptionai/jais-family-1p3b-chat" target="_blank">jais-family-1p3b-chat</a></td>
-        <td>35.39</td>
-        <td>32.51</td>
-        <td>38.33</td>
-        <td>45.29</td>
         <td>00.13</td>
         <td>06.18</td>
         <td>00.50</td>
+        <td>15.43</td>
+        <td>02.44</td>
+        <td>19.14</td>
+        <td>01.99</td>
+        <td>12.60</td>
+        <td>00.01</td>
+        <td>03.01</td>
+        <td>00.50</td>
+        <td>45.29</td>
     </tr>
     <tr>
         <td><a href="https://huggingface.co/inceptionai/jais-family-2p7b-chat" target="_blank">jais-family-2p7b-chat</a></td>
-        <td>37.44</td>
-        <td>34.49</td>
-        <td>44.11</td>
-        <td>51.56</td>
         <td>00.25</td>
         <td>07.46</td>
+        <td>00.62</td>
+        <td>16.36</td>
+        <td>04.25</td>
+        <td>18.22</td>
+        <td>03.10</td>
+        <td>08.19</td>
+        <td>00.01</td>
+        <td>03.27</td>
         <td>00.90</td>
+        <td>51.56</td>
     </tr>
     <tr>
         <td><a href="https://huggingface.co/google/gemma-2-2b-it" target="_blank">gemma-2-2b-it</a></td>
-        <td>28.58</td>
-        <td>32.42</td>
-        <td>25.22</td>
-        <td>53.36</td>
         <td>00.10</td>
         <td>04.96</td>
+        <td>00.12</td>
+        <td>06.66</td>
+        <td>01.55</td>
+        <td>18.59</td>
+        <td>02.78</td>
+        <td>23.69</td>
+        <td>00.01</td>
+        <td>02.08</td>
         <td>06.80</td>
+        <td>53.36</td>
+    </tr>
+    <tr>
+        <td><a href="meta-llama/Llama-3.2-1B-Instruct" target="_blank">Llama-3.2-1B-Instruct</a></td>
+        <td>00.07</td>
+        <td>05.95</td>
+        <td>00.80</td>
+        <td>18.71</td>
+        <td>04.53</td>
+        <td>18.39</td>
+        <td>04.52</td>
+        <td>17.06</td>
+        <td>00.02</td>
+        <td>03.74</td>
+        <td>08.23</td>
+        <td>46.27</td>
+    </tr>
+    <tr>
+        <td><a href="meta-llama/Llama-3.2-3B-Instruct" target="_blank">Llama-3.2-3B-Instruct</a></td>
+        <td>00.62</td>
+        <td>13.67</td>
+        <td>01.18</td>
+        <td>22.12</td>
+        <td>08.59</td>
+        <td>35.21</td>
+        <td>13.75</td>
+        <td>43.63</td>
+        <td>00.21</td>
+        <td>09.68</td>
+        <td>08.23</td>
+        <td>49.20</td>
     </tr>
     <tr>
         <td><strong><a href="https://huggingface.co/MBZUAI-Paris/Atlas-Chat-2B" target="_blank">Atlas-Chat-2B</a></strong></td>
-        <td><b>44.97</td>
-        <td><b>41.48</td>
-        <td><b>53.89</td>
-        <td><b>73.99</td>
         <td><b>22.76</td>
         <td><b>44.86</td>
+        <td><b>16.67</td>
+        <td><b>41.64</td>
+        <td><b>14.92</td>
+        <td><b>43.03</td>
+        <td><b>23.88</td>
+        <td><b>52.19</td>
+        <td><b>08.18</td>
+        <td><b>21.54</td>
         <td><b>55.22</td>
+        <td><b>73.99</td>
     </tr>
     <tr style="border-top: 4px solid;"></tr>
     <tr>
         <td><a href="https://huggingface.co/inceptionai/jais-family-6p7b-chat" target="_blank">jais-family-6p7b-chat</a></td>
-        <td>39.96</td>
-        <td>41.57</td>
-        <td>51.22</td>
-        <td>56.78</td>
         <td>00.73</td>
         <td>11.85</td>
+        <td>01.88</td>
+        <td>23.22</td>
+        <td>04.25</td>
+        <td>18.22</td>
+        <td>04.62</td>
+        <td>20.22</td>
+        <td>00.02</td>
+        <td>03.79</td>
         <td>03.02</td>
+        <td>56.78</td>
     </tr>
     <tr>
         <td><a href="https://huggingface.co/inceptionai/jais-adapted-7b-chat" target="_blank">jais-adapted-7b-chat</a></td>
-        <td>39.30</td>
-        <td>35.19</td>
-        <td>43.67</td>
-        <td>52.72</td>
         <td>00.60</td>
         <td>09.43</td>
+        <td>03.45</td>
+        <td>25.88</td>
+        <td>07.25</td>
+        <td>23.21</td>
+        <td>01.25</td>
+        <td>02.22</td>
+        <td>00.04</td>
+        <td>03.24</td>
         <td>02.82</td>
+        <td>52.72</td>
     </tr>
     <tr>
         <td><a href="https://huggingface.co/inceptionai/jais-family-13b-chat" target="_blank">jais-family-13b-chat</a></td>
-        <td>45.11</td>
-        <td>43.90</td>
-        <td>58.67</td>
-        <td>41.73</td>
         <td>00.92</td>
         <td>11.71</td>
+        <td>04.01</td>
+        <td>28.48</td>
+        <td>05.70</td>
+        <td>27.24</td>
+        <td>04.50</td>
+        <td>22.56</td>
+        <td>00.03</td>
+        <td>03.57</td>
         <td>01.77</td>
+        <td>41.73</td>
     </tr>
     <tr>
         <td><a href="https://huggingface.co/inceptionai/jais-adapted-13b-chat" target="_blank">jais-adapted-13b-chat</a></td>
-        <td>45.20</td>
-        <td>40.65</td>
-        <td>49.67</td>
-        <td>66.68</td>
         <td>00.87</td>
         <td>10.52</td>
+        <td>04.02</td>
+        <td>25.29</td>
+        <td>06.66</td>
+        <td>23.46</td>
+        <td>20.14</td>
+        <td>47.87</td>
+        <td>0.04</td>
+        <td>04.77</td>
         <td>01.92</td>
+        <td>66.68</td>
     </tr>
     <tr>
         <td><a href="https://huggingface.co/FreedomIntelligence/AceGPT-7B-chat" target="_blank">AceGPT-7b-chat</a></td>
-        <td>35.98</td>
-        <td>36.57</td>
-        <td>30.11</td>
-        <td>40.23</td>
         <td>00.44</td>
         <td>11.33</td>
+        <td>01.05</td>
+        <td>19.24</td>
+        <td>06.92</td>
+        <td>36.03</td>
+        <td>11.05</td>
+        <td>44.55</td>
+        <td>00.06</td>
+        <td>04.74</td>
         <td>02.28</td>
+        <td>40.23</td>
+    </tr> 
+    <tr>
+        <td><a href="https://huggingface.co/FreedomIntelligence/AceGPT-13B-chat" target="_blank">AceGPT-13b-chat</a></td>
+        <td>00.98</td>
+        <td>16.70</td>
+        <td>00.81</td>
+        <td>20.23</td>
+        <td>08.73</td>
+        <td>40.76</td>
+        <td>14.02</td>
+        <td>48.28</td>
+        <td>00.12</td>
+        <td>06.32</td>
+        <td>02.80</td>
+        <td>59.58</td>
+    </tr>
+    <tr>
+        <td><a href="https://huggingface.co/google/gemma-2-9b-it" target="_blank">gemma-2-9b-it</a></td>
+        <td>03.10</td>
+        <td>19.16</td>
+        <td>01.72</td>
+        <td>24.35</td>
+        <td>05.18</td>
+        <td>36.96</td>
+        <td>08.23</td>
+        <td>43.57</td>
+        <td>00.17</td>
+        <td>09.14</td>
+        <td>13.81</td>
+            <td>59.87</td>
+    </tr>
+    <tr>
+        <td><a href="meta-llama/Meta-Llama-3.1-8B-Instruct" target="_blank">Llama-3.1-8B-Instruct</a></td>
+        <td>00.92</td>
+        <td>14.19</td>
+        <td>01.46</td>
+        <td>23.82</td>
+        <td>08.89</td>
+        <td>33.08</td>
+        <td>11.85</td>
+        <td>35.51</td>
+        <td>00.11</td>
+        <td>06.02</td>
+        <td>01.28</td>
+        <td>44.08</td>
+    </tr>
+    <tr>
+        <td><strong><a href="https://huggingface.co/MBZUAI-Paris/Atlas-Chat-9B" target="_blank">Atlas-Chat-9B</a></strong></td>
+        <td><b>28.08</td>
+        <td><b>50.48</td>
+        <td><b>18.16</td>
+        <td><b>43.91</td>
+        <td><b>18.63</td>
+        <td><b>47.53</td>
+        <td><b>29.98</td>
+        <td><b>58.26</td>
+        <td><b>22.08</td>
+        <td><b>34.17</td>
+        <td><b>59.76</td>
+        <td><b>81.89</td>
+    </tr>
+    <tr style="border-top: 4px solid;"></tr>
+    <tr>
+        <td><a href="https://huggingface.co/inceptionai/jais-family-30b-8k-chat" target="_blank">jais-family-30b-8k-chat</a></td>
+        <td>01.10</td>
+        <td>14.40</td>
+        <td>01.67</td>
+        <td>23.37</td>
+        <td>08.52</td>
+        <td>35.41</td>
+        <td>13.71</td>
+        <td>41.33</td>
+        <td>00.05</td>
+        <td>04.48</td>
+        <td>00.46</td>
+        <td>56.73</td>
+    </tr>
+    <tr>
+        <td><a href="https://huggingface.co/google/gemma-2-27b-it" target="_blank">gemma-2-27b-it</a></td>
+        <td>00.67</td>
+        <td>13.04</td>
+        <td>01.74</td>
+        <td>24.63</td>
+        <td>05.17</td>
+        <td>37.08</td>
+        <td>07.36</td>
+        <td>42.49</td>
+        <td>00.03</td>
+        <td>04.94</td>
+        <td>11.10</td>
+        <td>57.59</td>
+    </tr>
+    <tr>
+        <td><strong><a href="https://huggingface.co/MBZUAI-Paris/Atlas-Chat-27B" target="_blank">Atlas-Chat-27B</a></strong></td>
+        <td><b>29.55</td>
+        <td><b>51.74</td>
+        <td><b>19.66</td>
+        <td><b>45.65</td>
+        <td><b>20.34</td>
+        <td><b>49.19</td>
+        <td><b>31.61</td>
+        <td><b>59.37</td>
+        <td><b>33.03</td>
+        <td><b>40.95</td>
+        <td><b>60.70</td>
+        <td>73.00</td>
+    </tr>
+
+
+    
+</table>
+-->
+
+## Evaluation
+The Atlas-Chat models were evaluated on a comprehensive suite of tasks using various datasets and benchmarks to assess their performance across multiple dimensions. These included tasks such as:
+
+* **DarijaMMLU:** A Darija version of ArabicMMLU and MMLU benchmarks translated from MSA and English respectively.
+* **DarijaHellaSwag:** A Darija version of HellaSwag.
+* **Belebele Ary_Arab:** Belebele is a multiple-choice machine reading comprehension dataset published by Facebook spanning 122 language variants. The Evaluation is done on the Ary_Arab part of Belebele that refers to Darija.
+* **DarijaAlpacaEval:** A Darija version of AlpacaEval translated to Darija and adapted to the Moroccan culture.
+* **Sentiment Analysis.**
+* **Translation:** Including six directions and four languages: Darija, MSA, English and French.
+* **Transliteration:** Transforming a sentence from Darija (written in Arabic characters) to Arabizi (Written in Latin characters) and vice-versa.
+* **Summarization.**
+
+The models were compared against a collection of existing open-source Arabic models to gauge their effectiveness, with a particular focus on performance in Darija. All scores are based on zero-shot performance. The prompts are written mainly in Darija. The metric used for DarijaMMLU, DarijaHellaSwag, Belebele Ary and Sentiment Analysis is the normalized accuracy. We used [Language Model Evaluation Harness](https://github.com/MBZUAI-Paris/lm-evaluation-harness-atlas-chat) to conduct these evaluations.
+
+**LLMs Benchmarks:**
+<table>
+    <tr>
+        <td>Model</td>
+        <td><a href="https://huggingface.co/datasets/MBZUAI-Paris/DarijaMMLU" target="_blank">DarijaMMLU</a></td>
+        <td><a href="MBZUAI-Paris/DarijaHellaSwag" target="_blank">DarijaHellaSwag</a></td>
+        <td ><a href="https://huggingface.co/datasets/facebook/belebele/viewer/ary_Arab" target="_blank">Belebele Ary</a></td>
+        <td ><a href="https://huggingface.co/datasets/MBZUAI-Paris/DarijaAlpacaEval" target="_blank">DarijaAlpacaEval</a></td>
+    </tr>
+    <tr>
+        <td><a href="https://huggingface.co/inceptionai/jais-family-1p3b-chat" target="_blank">jais-family-1p3b-chat</a></td>
+        <td>35.39</td>
+        <td>32.51</td>
+        <td>38.33</td>
+        <td>35.56</td>
+    </tr>
+    <tr>
+        <td><a href="https://huggingface.co/inceptionai/jais-family-2p7b-chat" target="_blank">jais-family-2p7b-chat</a></td>
+        <td>37.44</td>
+        <td>34.49</td>
+        <td>44.11</td>
+        <td>52.97</td>
+    </tr>
+    <tr>
+        <td><a href="https://huggingface.co/google/gemma-2-2b-it" target="_blank">gemma-2-2b-it</a></td>
+        <td>28.58</td>
+        <td>32.42</td>
+        <td>25.22</td>
+        <td>58.67</td>
+    </tr>
+    <tr>
+        <td><a href="meta-llama/Llama-3.2-1B-Instruct" target="_blank">Llama-3.2-1B-Instruct</a></td>
+        <td>27.66</td>
+        <td>26.88</td>
+        <td>28.89</td>
+        <td>23.57</td>
+    </tr>
+    <tr>
+        <td><a href="meta-llama/Llama-3.2-3B-Instruct" target="_blank">Llama-3.2-3B-Instruct</a></td>
+        <td>32.60</td>
+        <td>28.33</td>
+        <td>38.00</td>
+        <td>47.62</td>
+    </tr>
+    <tr>
+        <td><strong><a href="https://huggingface.co/MBZUAI-Paris/Atlas-Chat-2B" target="_blank">Atlas-Chat-2B</a></strong></td>
+        <td><b>44.97</b></td>
+        <td><b>41.48</b></td>
+        <td><b>53.89</b></td>
+        <td><b>92.31</b></td>
+    </tr>
+    <tr style="border-top: 4px solid;"></tr>
+    <tr>
+        <td><a href="https://huggingface.co/inceptionai/jais-family-6p7b-chat" target="_blank">jais-family-6p7b-chat</a></td>
+        <td>39.96</td>
+        <td>41.57</td>
+        <td>51.22</td>
+        <td>65.18</td>
+    </tr>
+    <tr>
+        <td><a href="https://huggingface.co/inceptionai/jais-adapted-7b-chat" target="_blank">jais-adapted-7b-chat</a></td>
+        <td>39.30</td>
+        <td>35.19</td>
+        <td>43.67</td>
+        <td>61.84</td>
+    </tr>
+    <tr>
+        <td><a href="https://huggingface.co/inceptionai/jais-family-13b-chat" target="_blank">jais-family-13b-chat</a></td>
+        <td>45.11</td>
+        <td>43.90</td>
+        <td>58.67</td>
+        <td>69.93</td>
+    </tr>
+    <tr>
+        <td><a href="https://huggingface.co/inceptionai/jais-adapted-13b-chat" target="_blank">jais-adapted-13b-chat</a></td>
+        <td>45.20</td>
+        <td>40.65</td>
+        <td>49.67</td>
+        <td>77.52</td>
+    </tr>
+    <tr>
+        <td><a href="https://huggingface.co/FreedomIntelligence/AceGPT-7B-chat" target="_blank">AceGPT-7b-chat</a></td>
+        <td>35.98</td>
+        <td>36.57</td>
+        <td>30.11</td>
+        <td>47.31</td>
     </tr>
     <tr>
         <td><a href="https://huggingface.co/FreedomIntelligence/AceGPT-13B-chat" target="_blank">AceGPT-13b-chat</a></td>
         <td>41.09</td>
         <td>38.35</td>
         <td>33.11</td>
-        <td>59.58</td>
-        <td>00.98</td>
-        <td>16.70</td>
-        <td>02.80</td>
+        <td>52.79</td>
     </tr>
     <tr>
         <td><a href="https://huggingface.co/google/gemma-2-9b-it" target="_blank">gemma-2-9b-it</a></td>
         <td>35.91</td>
         <td>42.43</td>
         <td>31.00</td>
-        <td>59.87</td>
-        <td>03.10</td>
-        <td>19.16</td>
-        <td>13.81</td>
+        <td>90.86</td>
     </tr>
     <tr>
         <td><a href="meta-llama/Meta-Llama-3.1-8B-Instruct" target="_blank">Llama-3.1-8B-Instruct</a></td>
         <td>44.13</td>
         <td>38.24</td>
         <td>47.00</td>
-        <td>44.08</td>
+        <td>78.08</td>
+    </tr>
+    <tr>
+        <td><strong><a href="https://huggingface.co/MBZUAI-Paris/Atlas-Chat-9B" target="_blank">Atlas-Chat-9B</a></strong></td>
+        <td><b>58.23</b></td>
+        <td><b>57.75</b></td>
+        <td><b>74.56</b></td>
+        <td><b>95.62</b></td>
+    </tr>
+    <tr style="border-top: 4px solid;"></tr>
+    <tr>
+        <td><a href="https://huggingface.co/inceptionai/jais-family-30b-8k-chat" target="_blank">jais-family-30b-8k-chat</a></td>
+        <td>51.88</td>
+        <td>35.61</td>
+        <td>65.67</td>
+        <td>24.64</td>
+    </tr>
+    <tr>
+        <td><a href="https://huggingface.co/google/gemma-2-27b-it" target="_blank">gemma-2-27b-it</a></td>
+        <td>36.47</td>
+        <td>37.04</td>
+        <td>35.78</td>
+        <td>95.07</td>
+    </tr>
+    <tr>
+        <td><strong><a href="https://huggingface.co/MBZUAI-Paris/Atlas-Chat-27B" target="_blank">Atlas-Chat-27B</a></strong></td>
+        <td><b>61.95</b></td>
+        <td><b>48.37</b></td>
+        <td><b>75.67</b></td>
+        <td><b>96.58</b></td>
+    </tr>
+</table>
+
+**Standard NLP Tasks:**
+<table>
+    <tr>
+        <td rowspan="2">Model</td>
+        <td colspan="2"><a href="https://huggingface.co/datasets/MBZUAI-Paris/DarijaBench" target="_blank">DODa-10k (Translation)</a></td>
+        <td colspan="2"><a href="https://huggingface.co/datasets/MBZUAI-Paris/DarijaBench" target="_blank">MADAR (Translation)</a></td>
+        <td colspan="2"><a href="https://huggingface.co/datasets/MBZUAI-Paris/DarijaBench" target="_blank">FLORES+ (Translation)</a></td>
+        <td colspan="2"><a href="https://huggingface.co/datasets/MBZUAI-Paris/DarijaBench" target="_blank">NLLB-Seed (Translation)</a></td>
+        <td colspan="2"><a href="https://huggingface.co/datasets/MBZUAI-Paris/DarijaBench" target="_blank">DODa-10k (Transliteration)</a></td>
+        <td rowspan="2"><a href="https://huggingface.co/datasets/MBZUAI-Paris/DarijaBench" target="_blank">MArSum (Summarization)</a><br/>(LLM as a judge)</td>
+        <td rowspan="2"><a href="https://huggingface.co/datasets/MBZUAI-Paris/DarijaBench" target="_blank">Sentiment Analysis</a></td>
+    </tr>
+    <tr>
+        <td>BLEU</td>
+        <td>chrF</td>
+        <td>BLEU</td>
+        <td>chrF</td>
+        <td>BLEU</td>
+        <td>chrF</td>
+        <td>BLEU</td>
+        <td>chrF</td>
+        <td>BLEU</td>
+        <td>chrF</td>
+    </tr>
+    <tr>
+        <td><a href="https://huggingface.co/inceptionai/jais-family-1p3b-chat" target="_blank">jais-family-1p3b-chat</a></td>
+        <td>00.13</td>
+        <td>06.18</td>
+        <td>00.50</td>
+        <td>15.43</td>
+        <td>02.44</td>
+        <td>19.14</td>
+        <td>01.99</td>
+        <td>12.60</td>
+        <td>00.01</td>
+        <td>03.01</td>
+        <td>00.50</td>
+        <td>45.29</td>
+    </tr>
+    <tr>
+        <td><a href="https://huggingface.co/inceptionai/jais-family-2p7b-chat" target="_blank">jais-family-2p7b-chat</a></td>
+        <td>00.25</td>
+        <td>07.46</td>
+        <td>00.62</td>
+        <td>16.36</td>
+        <td>04.25</td>
+        <td>18.22</td>
+        <td>03.10</td>
+        <td>08.19</td>
+        <td>00.01</td>
+        <td>03.27</td>
+        <td>00.90</td>
+        <td>51.56</td>
+    </tr>
+    <tr>
+        <td><a href="https://huggingface.co/google/gemma-2-2b-it" target="_blank">gemma-2-2b-it</a></td>
+        <td>00.10</td>
+        <td>04.96</td>
+        <td>00.12</td>
+        <td>06.66</td>
+        <td>01.55</td>
+        <td>18.59</td>
+        <td>02.78</td>
+        <td>23.69</td>
+        <td>00.01</td>
+        <td>02.08</td>
+        <td>06.80</td>
+        <td>53.36</td>
+    </tr>
+    <tr>
+        <td><a href="meta-llama/Llama-3.2-1B-Instruct" target="_blank">Llama-3.2-1B-Instruct</a></td>
+        <td>00.07</td>
+        <td>05.95</td>
+        <td>00.80</td>
+        <td>18.71</td>
+        <td>04.53</td>
+        <td>18.39</td>
+        <td>04.52</td>
+        <td>17.06</td>
+        <td>00.02</td>
+        <td>03.74</td>
+        <td>08.23</td>
+        <td>46.27</td>
+    </tr>
+    <tr>
+        <td><a href="meta-llama/Llama-3.2-3B-Instruct" target="_blank">Llama-3.2-3B-Instruct</a></td>
+        <td>00.62</td>
+        <td>13.67</td>
+        <td>01.18</td>
+        <td>22.12</td>
+        <td>08.59</td>
+        <td>35.21</td>
+        <td>13.75</td>
+        <td>43.63</td>
+        <td>00.21</td>
+        <td>09.68</td>
+        <td>08.23</td>
+        <td>49.20</td>
+    </tr>
+    <tr>
+        <td><strong><a href="https://huggingface.co/MBZUAI-Paris/Atlas-Chat-2B" target="_blank">Atlas-Chat-2B</a></strong></td>
+        <td><b>22.76</td>
+        <td><b>44.86</td>
+        <td><b>16.67</td>
+        <td><b>41.64</td>
+        <td><b>14.92</td>
+        <td><b>43.03</td>
+        <td><b>23.88</td>
+        <td><b>52.19</td>
+        <td><b>08.18</td>
+        <td><b>21.54</td>
+        <td><b>55.22</td>
+        <td><b>73.99</td>
+    </tr>
+    <tr style="border-top: 4px solid;"></tr>
+    <tr>
+        <td><a href="https://huggingface.co/inceptionai/jais-family-6p7b-chat" target="_blank">jais-family-6p7b-chat</a></td>
+        <td>00.73</td>
+        <td>11.85</td>
+        <td>01.88</td>
+        <td>23.22</td>
+        <td>04.25</td>
+        <td>18.22</td>
+        <td>04.62</td>
+        <td>20.22</td>
+        <td>00.02</td>
+        <td>03.79</td>
+        <td>03.02</td>
+        <td>56.78</td>
+    </tr>
+    <tr>
+        <td><a href="https://huggingface.co/inceptionai/jais-adapted-7b-chat" target="_blank">jais-adapted-7b-chat</a></td>
+        <td>00.60</td>
+        <td>09.43</td>
+        <td>03.45</td>
+        <td>25.88</td>
+        <td>07.25</td>
+        <td>23.21</td>
+        <td>01.25</td>
+        <td>02.22</td>
+        <td>00.04</td>
+        <td>03.24</td>
+        <td>02.82</td>
+        <td>52.72</td>
+    </tr>
+    <tr>
+        <td><a href="https://huggingface.co/inceptionai/jais-family-13b-chat" target="_blank">jais-family-13b-chat</a></td>
+        <td>00.92</td>
+        <td>11.71</td>
+        <td>04.01</td>
+        <td>28.48</td>
+        <td>05.70</td>
+        <td>27.24</td>
+        <td>04.50</td>
+        <td>22.56</td>
+        <td>00.03</td>
+        <td>03.57</td>
+        <td>01.77</td>
+        <td>41.73</td>
+    </tr>
+    <tr>
+        <td><a href="https://huggingface.co/inceptionai/jais-adapted-13b-chat" target="_blank">jais-adapted-13b-chat</a></td>
+        <td>00.87</td>
+        <td>10.52</td>
+        <td>04.02</td>
+        <td>25.29</td>
+        <td>06.66</td>
+        <td>23.46</td>
+        <td>20.14</td>
+        <td>47.87</td>
+        <td>0.04</td>
+        <td>04.77</td>
+        <td>01.92</td>
+        <td>66.68</td>
+    </tr>
+    <tr>
+        <td><a href="https://huggingface.co/FreedomIntelligence/AceGPT-7B-chat" target="_blank">AceGPT-7b-chat</a></td>
+        <td>00.44</td>
+        <td>11.33</td>
+        <td>01.05</td>
+        <td>19.24</td>
+        <td>06.92</td>
+        <td>36.03</td>
+        <td>11.05</td>
+        <td>44.55</td>
+        <td>00.06</td>
+        <td>04.74</td>
+        <td>02.28</td>
+        <td>40.23</td>
+    </tr> 
+    <tr>
+        <td><a href="https://huggingface.co/FreedomIntelligence/AceGPT-13B-chat" target="_blank">AceGPT-13b-chat</a></td>
+        <td>00.98</td>
+        <td>16.70</td>
+        <td>00.81</td>
+        <td>20.23</td>
+        <td>08.73</td>
+        <td>40.76</td>
+        <td>14.02</td>
+        <td>48.28</td>
+        <td>00.12</td>
+        <td>06.32</td>
+        <td>02.80</td>
+        <td>59.58</td>
+    </tr>
+    <tr>
+        <td><a href="https://huggingface.co/google/gemma-2-9b-it" target="_blank">gemma-2-9b-it</a></td>
+        <td>03.10</td>
+        <td>19.16</td>
+        <td>01.72</td>
+        <td>24.35</td>
+        <td>05.18</td>
+        <td>36.96</td>
+        <td>08.23</td>
+        <td>43.57</td>
+        <td>00.17</td>
+        <td>09.14</td>
+        <td>13.81</td>
+            <td>59.87</td>
+    </tr>
+    <tr>
+        <td><a href="meta-llama/Meta-Llama-3.1-8B-Instruct" target="_blank">Llama-3.1-8B-Instruct</a></td>
         <td>00.92</td>
         <td>14.19</td>
-        <td>01.28</td>
+        <td>01.46</td>
+        <td>23.82</td>
+        <td>08.89</td>
+        <td>33.08</td>
+        <td>11.85</td>
+        <td>35.51</td>
+        <td>00.11</td>
+        <td>06.02</td>
+        <td>16.14</td>
+        <td>44.08</td>
     </tr>
     <tr>
         <td><strong><a href="https://huggingface.co/MBZUAI-Paris/Atlas-Chat-9B" target="_blank">Atlas-Chat-9B</a></strong></td>
-        <td><b>58.23</td>
-        <td><b>57.75</td>
-        <td><b>74.56</td>
-        <td><b>81.89</td>
         <td><b>28.08</td>
         <td><b>50.48</td>
+        <td><b>18.16</td>
+        <td><b>43.91</td>
+        <td><b>18.63</td>
+        <td><b>47.53</td>
+        <td><b>29.98</td>
+        <td><b>58.26</td>
+        <td><b>22.08</td>
+        <td><b>34.17</td>
         <td><b>59.76</td>
+        <td><b>81.89</td>
+    </tr>
+    <tr style="border-top: 4px solid;"></tr>
+    <tr>
+        <td><a href="https://huggingface.co/inceptionai/jais-family-30b-8k-chat" target="_blank">jais-family-30b-8k-chat</a></td>
+        <td>01.10</td>
+        <td>14.40</td>
+        <td>01.67</td>
+        <td>23.37</td>
+        <td>08.52</td>
+        <td>35.41</td>
+        <td>13.71</td>
+        <td>41.33</td>
+        <td>00.05</td>
+        <td>04.48</td>
+        <td>00.46</td>
+        <td>56.73</td>
+    </tr>
+    <tr>
+        <td><a href="https://huggingface.co/google/gemma-2-27b-it" target="_blank">gemma-2-27b-it</a></td>
+        <td>00.67</td>
+        <td>13.04</td>
+        <td>01.74</td>
+        <td>24.63</td>
+        <td>05.17</td>
+        <td>37.08</td>
+        <td>07.36</td>
+        <td>42.49</td>
+        <td>00.03</td>
+        <td>04.94</td>
+        <td>11.10</td>
+        <td>57.59</td>
+    </tr>
+    <tr>
+        <td><strong><a href="https://huggingface.co/MBZUAI-Paris/Atlas-Chat-27B" target="_blank">Atlas-Chat-27B</a></strong></td>
+        <td><b>29.55</td>
+        <td><b>51.74</td>
+        <td><b>19.66</td>
+        <td><b>45.65</td>
+        <td><b>20.34</td>
+        <td><b>49.19</td>
+        <td><b>31.61</td>
+        <td><b>59.37</td>
+        <td><b>33.03</td>
+        <td><b>40.95</td>
+        <td><b>60.70</td>
+        <td>73.00</td>
     </tr>
 
 
     
 </table>
 
-
 ## Usage and Limitations
 
 These models have certain limitations that users should be aware of.