Text Generation
Transformers
Safetensors
Egyptian Arabic
gemma3_text
conversational
text-generation-inference
amr-mohamed commited on
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663ae82
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Added model card

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  1. README.md +178 -249
README.md CHANGED
@@ -8,7 +8,7 @@ tags:
8
  language:
9
  - arz
10
  datasets:
11
- - MBZUAI-Paris/Egyptian-SFT
12
  base_model:
13
  - google/gemma-3-4b-pt
14
  ---
@@ -41,7 +41,6 @@ pip install -U transformers sentencepiece
41
  Then, copy the snippet from the section below.
42
 
43
  #### Running with the `pipeline` API
44
-
45
  ```python
46
  import torch
47
  from transformers import pipeline
@@ -53,6 +52,9 @@ pipe = pipeline(
53
  device="cuda" # replace with "mps" to run on a Mac device
54
  )
55
 
 
 
 
56
  messages = [
57
  {"role": "user", "content": 'اسمك ايه؟'},
58
  ]
@@ -61,11 +63,23 @@ outputs = pipe(messages, max_new_tokens=256)
61
  assistant_response = outputs[0]["generated_text"][-1]["content"].strip()
62
  print(assistant_response)
63
  ```
64
-
65
- - Response:
66
 
67
  >اسمي نايل-شات، على اسم نهر النيل، اطول نهر في العالم، اللي من زمان كان عامل مهم في تطور مصر، وبيساعد في معيشة الناس وأثر على التراث والثقافة بتاعتنا. وعشان انا موديل لغة، الباحثين بتوع جامعة محمد بن زايد للذكاء الاصطناعي دربوني باستخدام مجموعة من المصادر المفتوحة، فدي حاجة خلتني مميز.
68
 
 
 
 
 
 
 
 
 
 
 
 
 
 
69
  ## Training Data
70
  Nile-Chat models were trained on diverse datasets focusing on Egyptian dialect consisting of approximately 3.3B tokens during continual pre-training phase, 1.9M instructions during instruction finetuning and 0.2M samples for DPO, with a maximum length of 2048 tokens, including:
71
 
@@ -73,7 +87,7 @@ Nile-Chat models were trained on diverse datasets focusing on Egyptian dialect c
73
  * Instruction samples created from publicly available Egyptian Arabic datasets including translation and transliteration.
74
  * Translated English and multi-lingual pretraining and instruction-tuning datasets using Claude 3.5 Sonnet (v2).
75
 
76
- The dataset covers both Egyptian Arabic and Latin scripts. Our instruction tuning dataset [Egyptian-SFT](https://huggingface.co/datasets/MBZUAI-Paris/Egyptian-SFT) is publicly available.
77
 
78
 
79
  ## Implementation Information
@@ -91,288 +105,202 @@ Nile-Chat models were evaluated on a comprehensive suite of tasks using various
91
  * **EgyptianWinoGrande:** An Egyptian version of WinoGrande benchmark (In both scripts Arabic and Latin).
92
  * **EgyptianRACE:** An Egyptian version of RACE benchmark (In both scripts Arabic and Latin).
93
  * **EgyptianOpenBookQA:** An Egyptian version of OpenBookQA benchmark.
 
94
 
95
  The models were compared against a collection of existing open-source Arabic models to gauge their effectiveness, with a particular focus on performance in Egyptian. All scores are based on zero-shot performance. The prompts are written mainly in Egyptian. We used [Language Model Evaluation Harness](https://github.com/MBZUAI-Paris/lm-evaluation-harness-nile-chat) to conduct these evaluations. All evaluations are done with applying chat template except for EgyptianWinoGrande.
96
 
97
- **Benchmarks:**
 
98
  <table>
 
99
  <tr>
100
- <td>Model</td>
101
- <td>Average</td>
102
- <td><a href="https://huggingface.co/datasets/MBZUAI-Paris/EgyptianMMLU_dev" target="_blank">EgyptianMMLU</a></td>
103
- <td ><a href="https://huggingface.co/datasets/facebook/belebele/viewer/ary_Arab" target="_blank">Belebele Arz</a></td>
104
- <td><a href="https://huggingface.co/datasets/MBZUAI-Paris/EgyptianHellaSwag" target="_blank">EgyptianHellaSwag</br>(Arabic Script)</a></td>
105
- <td ><a href="https://huggingface.co/datasets/MBZUAI-Paris/EgyptianPIQA" target="_blank">EgyptianPIQA</br>(Arabic Script)</a></td>
106
- <td ><a href="https://huggingface.co/datasets/MBZUAI-Paris/EgyptianWinoGrande" target="_blank">EgyptianWinoGrande</br>(Arabic Script)</a></td>
107
- <td ><a href="https://huggingface.co/datasets/MBZUAI-Paris/EgyptianOpenBookQA" target="_blank">EgyptianOpenBookQA</a></td>
108
- <td ><a href="https://huggingface.co/datasets/MBZUAI-Paris/EgyptianRACE" target="_blank">EgyptianRACE High</br>(Arabic Script)</a></td>
109
- <td ><a href="https://huggingface.co/datasets/MBZUAI-Paris/EgyptianRACE" target="_blank">EgyptianRACE Middle</br>(Arabic Script)</a></td>
110
- <td ><a href="https://huggingface.co/datasets/MBZUAI-Paris/EgyptianHellaSwag" target="_blank">EgyptianHellaSwag</br>(Latin Script)</a></td>
111
- <td ><a href="https://huggingface.co/datasets/MBZUAI-Paris/EgyptianPIQA" target="_blank">EgyptianPIQA</br>(Latin Script)</a></td>
112
- <td ><a href="https://huggingface.co/datasets/MBZUAI-Paris/EgyptianWinoGrande" target="_blank">EgyptianWinoGrande</br>(Latin Script)</a></td>
113
- <td ><a href="https://huggingface.co/datasets/MBZUAI-Paris/EgyptianRACE" target="_blank">EgyptianRACE High</br>(Latin Script)</a></td>
114
- <td ><a href="https://huggingface.co/datasets/MBZUAI-Paris/EgyptianRACE" target="_blank">EgyptianRACE Middle</br>(Latin Script)</a></td>
115
  </tr>
 
 
116
  <tr>
117
- <td><a href="https://huggingface.co/google/gemma-3-4b-it" target="_blank">gemma-3-4b-it</a></td>
118
- <td>41.4</td>
119
- <td>46.08</td>
120
- <td>38.56</td>
121
- <td>42.56</td>
122
- <td>60.32</td>
123
- <td>56.49</td>
124
- <td>35.79</td>
125
- <td>33.68</td>
126
- <td>40.06</td>
127
- <td>30.90</td>
128
- <td>52.76</td>
129
- <td>48.57</td>
130
- <td>25.47</td>
131
- <td>26.94</td>
132
  </tr>
133
  <tr>
134
- <td><a href="https://huggingface.co/inceptionai/jais-family-6p7b-chat" target="_blank">jais-family-6p7b-chat</a></td>
135
- <td>43.22</td>
136
- <td>42.6</td>
137
- <td>57.33</td>
138
- <td>49.18</td>
139
- <td>62.23</td>
140
- <td>57.04</td>
141
- <td>33.33</td>
142
- <td>34.72</td>
143
- <td>37.5</td>
144
- <td>30.27</td>
145
- <td>53.25</td>
146
- <td>52.14</td>
147
- <td>24.18</td>
148
- <td>28.06</td>
149
  </tr>
150
  <tr>
151
- <td><a href="https://huggingface.co/inceptionai/jais-adapted-7b-chat" target="_blank">jais-adapted-7b-chat</a></td>
152
- <td>41.81</td>
153
- <td>40.96</td>
154
- <td>55.67</td>
155
- <td>40.85</td>
156
- <td>56.5</td>
157
- <td>54.35</td>
158
- <td>32.89</td>
159
- <td>34.62</td>
160
- <td>42.33</td>
161
- <td>30.81</td>
162
- <td>51.67</td>
163
- <td>50.4</td>
164
- <td>24.38</td>
165
- <td>28.06</td>
166
  </tr>
167
  <tr>
168
- <td><a href="https://huggingface.co/Qwen/Qwen2.5-7B-Instruct" target="_blank">Qwen2.5-7B-Instruct</a></td>
169
- <td>43.85</td>
170
- <td>45.74</td>
171
- <td>64.22</td>
172
- <td>45.47</td>
173
- <td>58.02</td>
174
- <td>56.41</td>
175
- <td>38.7</td>
176
- <td>35.45</td>
177
- <td>41.76</td>
178
- <td>30.51</td>
179
- <td>51.88</td>
180
- <td>50.95</td>
181
- <td>24.88</td>
182
- <td>26.11</td>
183
  </tr>
184
  <tr>
185
- <td><a href="https://huggingface.co/ALLaM-AI/ALLaM-7B-Instruct-preview" target="_blank">ALLaM-7B-Instruct-preview</a></td>
186
- <td>48.53</td>
187
- <td>60.08</td>
188
- <td>67.67</td>
189
- <td>57.29</td>
190
- <td>66.1</td>
191
- <td>62.18</td>
192
- <td>40.04</td>
193
- <td>39.5</td>
194
- <td>45.17</td>
195
- <td>32.17</td>
196
- <td>53.09</td>
197
- <td>50.63</td>
198
- <td>25.07</td>
199
- <td>31.94</td>
200
  </tr>
201
  <tr>
202
- <td><a href="https://huggingface.co/CohereLabs/c4ai-command-r7b-arabic-02-2025" target="_blank">c4ai-command-r7b-arabic-02-2025</a></td>
203
- <td>46.27</td>
204
- <td>50.97</td>
205
- <td>70.67</td>
206
- <td>50.39</td>
207
- <td>61.84</td>
208
- <td>57.2</td>
209
- <td>36.91</td>
210
- <td>41.89</td>
211
- <td>46.02</td>
212
- <td>30.88</td>
213
- <td>52.32</td>
214
- <td>51.43</td>
215
- <td>25.07</td>
216
- <td>27.22</td>
217
  </tr>
218
- <!-- <tr style="border-top: 4px solid;"></tr> -->
219
  <tr>
220
- <td><a href="https://huggingface.co/meta-llama/Meta-Llama-3.1-8B-Instruct" target="_blank">Llama-3.1-8B-Instruct</a></td>
221
- <td>42.5</td>
222
- <td>42.88</td>
223
- <td>55.89</td>
224
- <td>43.1</td>
225
- <td>57.97</td>
226
- <td>54.27</td>
227
- <td>35.57</td>
228
- <td>34.41</td>
229
- <td>40.34</td>
230
- <td>31.77</td>
231
- <td>53.3</td>
232
- <td>50.24</td>
233
- <td>24.48</td>
234
- <td>28.33</td>
235
  </tr>
236
  <tr>
237
- <td><a href="https://huggingface.co/FreedomIntelligence/AceGPT-v2-8B-chat" target="_blank">AceGPT-v2-8b-chat</a></td>
238
- <td>48.04</td>
239
- <td>55.25</td>
240
- <td>73.33</td>
241
- <td>53.14</td>
242
- <td>62.5</td>
243
- <td>58.39</td>
244
- <td>39.82</td>
245
- <td>41.06</td>
246
- <td>47.16</td>
247
- <td>33.16</td>
248
- <td>53.8</td>
249
- <td>50.24</td>
250
- <td>26.07</td>
251
- <td>30.56</td>
252
  </tr>
253
  <tr>
254
- <td><a href="https://huggingface.co/google/gemma-2-9b-it" target="_blank">gemma-2-9b-it</a></td>
255
- <td>45.41</td>
256
- <td>50.72</td>
257
- <td>49.44</td>
258
- <td>49.53</td>
259
- <td>61.35</td>
260
- <td>61.79</td>
261
- <td>35.79</td>
262
- <td>40.23</td>
263
- <td>48.01</td>
264
- <td>33.75</td>
265
- <td>53.69</td>
266
- <td>50.79</td>
267
- <td>26.66</td>
268
- <td>28.61</td>
269
  </tr>
270
  <tr>
271
- <td><a href="https://huggingface.co/google/gemma-3-12b-it" target="_blank">gemma-3-12b-it</a></td>
272
- <td>50.22</td>
273
- <td>61.55</td>
274
- <td>77</td>
275
- <td>49.49</td>
276
- <td>64.96</td>
277
- <td>63.53</td>
278
- <td>38.03</td>
279
- <td>41.27</td>
280
- <td>48.86</td>
281
- <td>37.52</td>
282
- <td>53.14</td>
283
- <td>51.19</td>
284
- <td>31.02</td>
285
- <td>35.28</td>
286
  </tr>
287
  <tr>
288
- <td><a href="https://huggingface.co/inceptionai/jais-family-13b-chat" target="_blank">jais-family-13b-chat</a></td>
289
- <td>44.66</td>
290
- <td>44.85</td>
291
- <td>66.33</td>
292
- <td>52.99</td>
293
- <td>64.85</td>
294
- <td>57.91</td>
295
- <td>36.91</td>
296
- <td>33.26</td>
297
- <td>38.64</td>
298
- <td>30.46</td>
299
- <td>53.09</td>
300
- <td>48.18</td>
301
- <td>25.28</td>
302
- <td>27.78</td>
303
  </tr>
304
  <tr>
305
- <td><a href="https://huggingface.co/inceptionai/jais-adapted-13b-chat" target="_blank">jais-adapted-13b-chat</a></td>
306
- <td>44.63</td>
307
- <td>50.03</td>
308
- <td>65.33</td>
309
- <td>47.53</td>
310
- <td>61.3</td>
311
- <td>56.72</td>
312
- <td>37.14</td>
313
- <td>35.45</td>
314
- <td>41.76</td>
315
- <td>31.14</td>
316
- <td>52.87</td>
317
- <td>50.79</td>
318
- <td>23.98</td>
319
- <td>26.11</td>
320
  </tr>
321
  <tr>
322
- <td><a href="https://huggingface.co/Qwen/Qwen2.5-14B-Instruct" target="_blank">Qwen2.5-14B-Instruct</a></td>
323
- <td>49.39</td>
324
- <td>60.81</td>
325
- <td>72.33</td>
326
- <td>55.84</td>
327
- <td>63.97</td>
328
- <td>59.97</td>
329
- <td>38.26</td>
330
- <td>43.25</td>
331
- <td>50.28</td>
332
- <td>33.49</td>
333
- <td>52.87</td>
334
- <td>53.41</td>
335
- <td>27.35</td>
336
- <td>30.28</td>
337
  </tr>
338
  <tr style="border-top: 4px solid;"></tr>
339
  <tr>
340
- <td><strong><a href="https://huggingface.co/MBZUAI-Paris/Nile-Chat-4B" target="_blank">Nile-Chat-4B</a></td>
341
- <td>53.07</td>
342
- <td>50.25</td>
343
- <td>68.56</td>
344
- <td>55.92</td>
345
- <td>67.3</td>
346
- <td>61.87</td>
347
- <td>40.94</td>
348
- <td>42.1</td>
349
- <td>46.02</td>
350
- <td>50.55</td>
351
- <td>65.32</td>
352
- <td>60.62</td>
353
- <td>37.36</td>
354
- <td>43.06</td>
355
  </tr>
356
  <tr>
357
- <td><strong><a href="https://huggingface.co/MBZUAI-Paris/Nile-Chat-12B" target="_blank">Nile-Chat-12B</a></td>
358
- <td>57.92</td>
359
- <td>62.59</td>
360
- <td>79.44</td>
361
- <td>64.04</td>
362
- <td>70.69</td>
363
- <td>63.53</td>
364
- <td>42.06</td>
365
- <td>48.02</td>
366
- <td>53.13</td>
367
- <td>53.71</td>
368
- <td>65.1</td>
369
- <td>59.98</td>
370
- <td>41.72</td>
371
- <td>48.89</td>
372
  </tr>
 
373
  </table>
374
 
375
- **Translation and Transliteration Tasks:**
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
376
  <table>
377
  <tr>
378
  <td rowspan="2">Model</td>
@@ -577,6 +505,7 @@ The models were compared against a collection of existing open-source Arabic mod
577
 
578
  </table>
579
 
 
580
  ## Usage and Limitations
581
 
582
  These models have certain limitations that users should be aware of.
@@ -663,4 +592,4 @@ Risks identified and mitigations:
663
  (Personally Identifiable Information). Developers are encouraged to adhere to
664
  privacy regulations with privacy-preserving techniques.
665
 
666
- </details>
 
8
  language:
9
  - arz
10
  datasets:
11
+ - MBZUAI-Paris/Egyptian-SFT-Mixture
12
  base_model:
13
  - google/gemma-3-4b-pt
14
  ---
 
41
  Then, copy the snippet from the section below.
42
 
43
  #### Running with the `pipeline` API
 
44
  ```python
45
  import torch
46
  from transformers import pipeline
 
52
  device="cuda" # replace with "mps" to run on a Mac device
53
  )
54
 
55
+ ```
56
+ Q1:
57
+ ```
58
  messages = [
59
  {"role": "user", "content": 'اسمك ايه؟'},
60
  ]
 
63
  assistant_response = outputs[0]["generated_text"][-1]["content"].strip()
64
  print(assistant_response)
65
  ```
66
+ A1:
 
67
 
68
  >اسمي نايل-شات، على اسم نهر النيل، اطول نهر في العالم، اللي من زمان كان عامل مهم في تطور مصر، وبيساعد في معيشة الناس وأثر على التراث والثقافة بتاعتنا. وعشان انا موديل لغة، الباحثين بتوع جامعة محمد بن زايد للذكاء الاصطناعي دربوني باستخدام مجموعة من المصادر المفتوحة، فدي حاجة خلتني مميز.
69
 
70
+ Q2:
71
+ ```python
72
+ messages = [
73
+ {"role": "user", "content": 'Esmak eh?'},
74
+ ]
75
+ outputs = pipe(messages, max_new_tokens=256)
76
+ assistant_response = outputs[0]["generated_text"][-1]["content"].strip()
77
+ print(assistant_response)
78
+ ```
79
+ A2:
80
+
81
+ >Esmi Nile-Chat, 3ala esm nahr el-nil, atwal nahr fel 3alam, elli men zaman kan 3amel mohemm fi tatwor masr, w bir3a el nas, w tb3an el torath
82
+
83
  ## Training Data
84
  Nile-Chat models were trained on diverse datasets focusing on Egyptian dialect consisting of approximately 3.3B tokens during continual pre-training phase, 1.9M instructions during instruction finetuning and 0.2M samples for DPO, with a maximum length of 2048 tokens, including:
85
 
 
87
  * Instruction samples created from publicly available Egyptian Arabic datasets including translation and transliteration.
88
  * Translated English and multi-lingual pretraining and instruction-tuning datasets using Claude 3.5 Sonnet (v2).
89
 
90
+ The dataset covers both Egyptian Arabic and Latin scripts. Our instruction tuning dataset [Egyptian-SFT-Mixture](https://huggingface.co/datasets/MBZUAI-Paris/Egyptian-SFT-Mixture) is publicly available.
91
 
92
 
93
  ## Implementation Information
 
105
  * **EgyptianWinoGrande:** An Egyptian version of WinoGrande benchmark (In both scripts Arabic and Latin).
106
  * **EgyptianRACE:** An Egyptian version of RACE benchmark (In both scripts Arabic and Latin).
107
  * **EgyptianOpenBookQA:** An Egyptian version of OpenBookQA benchmark.
108
+ * **EgyptianAlpacaEval:** An Egyptian adaptation of AlpacaEval to assess LLM instruction-following and cultural alignment.
109
 
110
  The models were compared against a collection of existing open-source Arabic models to gauge their effectiveness, with a particular focus on performance in Egyptian. All scores are based on zero-shot performance. The prompts are written mainly in Egyptian. We used [Language Model Evaluation Harness](https://github.com/MBZUAI-Paris/lm-evaluation-harness-nile-chat) to conduct these evaluations. All evaluations are done with applying chat template except for EgyptianWinoGrande.
111
 
112
+ ## Benchmarks:
113
+ ### Arabic Script Benchmarks
114
  <table>
115
+ <thead>
116
  <tr>
117
+ <th><a href="#">Model</a></th>
118
+ <th>Average</th>
119
+ <th><a href="https://huggingface.co/datasets/MBZUAI-Paris/EgyptianMMLU_dev" target="_blank">EgyptianMMLU</a></th>
120
+ <th><a href="https://huggingface.co/datasets/facebook/belebele/viewer/ary_Arab" target="_blank">Belebele Arz</a></th>
121
+ <th><a href="https://huggingface.co/datasets/MBZUAI-Paris/EgyptianHellaSwag" target="_blank">EgyptianHellaSwag</a></th>
122
+ <th><a href="https://huggingface.co/datasets/MBZUAI-Paris/EgyptianPIQA" target="_blank">EgyptianPIQA</a></th>
123
+ <th><a href="https://huggingface.co/datasets/MBZUAI-Paris/EgyptianWinoGrande" target="_blank">EgyptianWinoGrande</a></th>
124
+ <th><a href="https://huggingface.co/datasets/MBZUAI-Paris/EgyptianOpenBookQA" target="_blank">EgyptianOpenBookQA</a></th>
125
+ <th><a href="https://huggingface.co/datasets/MBZUAI-Paris/EgyptianRACE" target="_blank">EgyptianRACE High</a></th>
126
+ <th><a href="https://huggingface.co/datasets/MBZUAI-Paris/EgyptianRACE" target="_blank">EgyptianRACE Middle</a></th>
127
+ <th><a href="https://huggingface.co/datasets/MBZUAI-Paris/EgyptianAlpacaEval" target="_blank">EgyptianAlpacaEval</a></th>
 
 
 
 
128
  </tr>
129
+ </thead>
130
+ <tbody>
131
  <tr>
132
+ <td><a href="https://huggingface.co/google/gemma-3-4b-it" target="_blank">gemma-3-4b-it</a></td>
133
+ <td>48.76</td>
134
+ <td>46.08</td><td>38.56</td><td>42.56</td><td>60.32</td><td>56.49</td><td>35.79</td><td>33.68</td><td>40.06</td><td>85.30</td>
 
 
 
 
 
 
 
 
 
 
 
 
135
  </tr>
136
  <tr>
137
+ <td><a href="https://huggingface.co/inceptionai/jais-family-6p7b-chat" target="_blank">jais-family-6p7b-chat</a></td>
138
+ <td>46.64</td>
139
+ <td>42.60</td><td>57.33</td><td>49.18</td><td>62.23</td><td>57.04</td><td>33.33</td><td>34.72</td><td>37.50</td><td>45.86</td>
 
 
 
 
 
 
 
 
 
 
 
 
140
  </tr>
141
  <tr>
142
+ <td><a href="https://huggingface.co/inceptionai/jais-adapted-7b-chat" target="_blank">jais-adapted-7b-chat</a></td>
143
+ <td>42.18</td>
144
+ <td>40.96</td><td>55.67</td><td>40.85</td><td>56.50</td><td>54.35</td><td>32.89</td><td>34.62</td><td>42.33</td><td>21.45</td>
 
 
 
 
 
 
 
 
 
 
 
 
145
  </tr>
146
  <tr>
147
+ <td><a href="https://huggingface.co/Qwen/Qwen2.5-7B-Instruct" target="_blank">Qwen2.5-7B-Instruct</a></td>
148
+ <td>49.40</td>
149
+ <td>45.74</td><td>64.22</td><td>45.47</td><td>58.02</td><td>56.41</td><td>38.70</td><td>35.45</td><td>41.76</td><td>58.80</td>
 
 
 
 
 
 
 
 
 
 
 
 
150
  </tr>
151
  <tr>
152
+ <td><a href="https://huggingface.co/ALLaM-AI/ALLaM-7B-Instruct-preview" target="_blank">ALLaM-7B-Instruct-preview</a></td>
153
+ <td>56.40</td>
154
+ <td>60.08</td><td>67.67</td><td>57.29</td><td>66.10</td><td>62.18</td><td>40.04</td><td>39.50</td><td>45.17</td><td>69.55</td>
 
 
 
 
 
 
 
 
 
 
 
 
155
  </tr>
156
  <tr>
157
+ <td><a href="https://huggingface.co/CohereLabs/c4ai-command-r7b-arabic-02-2025" target="_blank">c4ai-command-r7b-arabic-02-2025</a></td>
158
+ <td>53.36</td>
159
+ <td>50.97</td><td>70.67</td><td>50.39</td><td>61.84</td><td>57.20</td><td>36.91</td><td>41.89</td><td>46.02</td><td>73.36</td>
 
 
 
 
 
 
 
 
 
 
 
 
160
  </tr>
 
161
  <tr>
162
+ <td><a href="https://huggingface.co/meta-llama/Meta-Llama-3.1-8B-Instruct" target="_blank">Llama-3.1-8B-Instruct</a></td>
163
+ <td>46.31</td>
164
+ <td>42.88</td><td>55.89</td><td>43.10</td><td>57.97</td><td>54.27</td><td>35.57</td><td>34.41</td><td>40.34</td><td>52.35</td>
 
 
 
 
 
 
 
 
 
 
 
 
165
  </tr>
166
  <tr>
167
+ <td><a href="https://huggingface.co/FreedomIntelligence/AceGPT-v2-8B-chat" target="_blank">AceGPT-v2-8b-chat</a></td>
168
+ <td>58.33</td>
169
+ <td>55.25</td><td>73.33</td><td>53.14</td><td>62.50</td><td>58.39</td><td>39.82</td><td>41.06</td><td>47.16</td><td>93.33</td>
 
 
 
 
 
 
 
 
 
 
 
 
170
  </tr>
171
  <tr>
172
+ <td><a href="https://huggingface.co/google/gemma-2-9b-it" target="_blank">gemma-2-9b-it</a></td>
173
+ <td>53.17</td>
174
+ <td>50.72</td><td>49.44</td><td>49.53</td><td>61.35</td><td>61.79</td><td>35.79</td><td>40.23</td><td>48.01</td><td>81.66</td>
 
 
 
 
 
 
 
 
 
 
 
 
175
  </tr>
176
  <tr>
177
+ <td><a href="https://huggingface.co/google/gemma-3-12b-it" target="_blank">gemma-3-12b-it</a></td>
178
+ <td>59.70</td>
179
+ <td>61.55</td><td>77.00</td><td>49.49</td><td>64.96</td><td>63.53</td><td>38.03</td><td>41.27</td><td>48.86</td><td>92.61</td>
 
 
 
 
 
 
 
 
 
 
 
 
180
  </tr>
181
  <tr>
182
+ <td><a href="https://huggingface.co/inceptionai/jais-family-13b-chat" target="_blank">jais-family-13b-chat</a></td>
183
+ <td>49.81</td>
184
+ <td>44.85</td><td>66.33</td><td>52.99</td><td>64.85</td><td>57.91</td><td>36.91</td><td>33.26</td><td>38.64</td><td>52.52</td>
 
 
 
 
 
 
 
 
 
 
 
 
185
  </tr>
186
  <tr>
187
+ <td><a href="https://huggingface.co/inceptionai/jais-adapted-13b-chat" target="_blank">jais-adapted-13b-chat</a></td>
188
+ <td>49.80</td>
189
+ <td>50.03</td><td>65.33</td><td>47.53</td><td>61.30</td><td>56.72</td><td>37.14</td><td>35.45</td><td>41.76</td><td>52.91</td>
 
 
 
 
 
 
 
 
 
 
 
 
190
  </tr>
191
  <tr>
192
+ <td><a href="https://huggingface.co/Qwen/Qwen2.5-14B-Instruct" target="_blank">Qwen2.5-14B-Instruct</a></td>
193
+ <td>57.34</td>
194
+ <td>60.81</td><td>72.33</td><td>55.84</td><td>63.97</td><td>59.97</td><td>38.26</td><td>43.25</td><td>50.28</td><td>71.35</td>
 
 
 
 
 
 
 
 
 
 
 
 
195
  </tr>
196
  <tr style="border-top: 4px solid;"></tr>
197
  <tr>
198
+ <td><a href="https://huggingface.co/MBZUAI-Paris/Nile-Chat-4B" target="_blank"><strong>Nile-Chat-4B</strong></a></td>
199
+ <td>57.85</td>
200
+ <td>50.25</td><td>68.56</td><td>55.92</td><td>67.30</td><td>61.87</td><td>40.94</td><td>42.10</td><td>46.02</td><td>87.65</td>
 
 
 
 
 
 
 
 
 
 
 
 
201
  </tr>
202
  <tr>
203
+ <td><a href="https://huggingface.co/MBZUAI-Paris/Nile-Chat-12B" target="_blank"><strong>Nile-Chat-12B</strong></a></td>
204
+ <td>64.11</td>
205
+ <td>62.59</td><td>79.44</td><td>64.04</td><td>70.69</td><td>63.53</td><td>42.06</td><td>48.02</td><td>53.13</td><td>93.50</td>
 
 
 
 
 
 
 
 
 
 
 
 
206
  </tr>
207
+ </tbody>
208
  </table>
209
 
210
+ ### Latin Script Benchmarks
211
+ <table>
212
+ <thead>
213
+ <tr>
214
+ <th><a href="#">Model</a></th>
215
+ <th>Average</th>
216
+ <th><a href="https://huggingface.co/datasets/MBZUAI-Paris/EgyptianHellaSwag" target="_blank">EgyptianHellaSwag</a></th>
217
+ <th><a href="https://huggingface.co/datasets/MBZUAI-Paris/EgyptianPIQA" target="_blank">EgyptianPIQA</a></th>
218
+ <th><a href="https://huggingface.co/datasets/MBZUAI-Paris/EgyptianWinoGrande" target="_blank">EgyptianWinoGrande</a></th>
219
+ <th><a href="https://huggingface.co/datasets/MBZUAI-Paris/EgyptianRACE" target="_blank">EgyptianRACE High</a></th>
220
+ <th><a href="https://huggingface.co/datasets/MBZUAI-Paris/EgyptianRACE" target="_blank">EgyptianRACE Middle</a></th>
221
+ </tr>
222
+ </thead>
223
+ <tbody>
224
+ <tr>
225
+ <td><a href="https://huggingface.co/google/gemma-3-4b-it" target="_blank">gemma-3-4b-it</a></td>
226
+ <td>36.93</td>
227
+ <td>30.90</td><td>52.76</td><td>48.57</td><td>25.47</td><td>26.94</td>
228
+ </tr>
229
+ <tr>
230
+ <td><a href="https://huggingface.co/inceptionai/jais-family-6p7b-chat" target="_blank">jais-family-6p7b-chat</a></td>
231
+ <td>37.58</td>
232
+ <td>30.27</td><td>53.25</td><td>52.14</td><td>24.18</td><td>28.06</td>
233
+ </tr>
234
+ <tr>
235
+ <td><a href="https://huggingface.co/inceptionai/jais-adapted-7b-chat" target="_blank">jais-adapted-7b-chat</a></td>
236
+ <td>37.06</td>
237
+ <td>30.81</td><td>51.67</td><td>50.40</td><td>24.38</td><td>28.06</td>
238
+ </tr>
239
+ <tr>
240
+ <td><a href="https://huggingface.co/Qwen/Qwen2.5-7B-Instruct" target="_blank">Qwen2.5-7B-Instruct</a></td>
241
+ <td>36.87</td>
242
+ <td>30.51</td><td>51.88</td><td>50.95</td><td>24.88</td><td>26.11</td>
243
+ </tr>
244
+ <tr>
245
+ <td><a href="https://huggingface.co/ALLaM-AI/ALLaM-7B-Instruct-preview" target="_blank">ALLaM-7B-Instruct-preview</a></td>
246
+ <td>38.58</td>
247
+ <td>32.17</td><td>53.09</td><td>50.63</td><td>25.07</td><td>31.94</td>
248
+ </tr>
249
+ <tr>
250
+ <td><a href="https://huggingface.co/CohereLabs/c4ai-command-r7b-arabic-02-2025" target="_blank">c4ai-command-r7b-arabic-02-2025</a></td>
251
+ <td>37.38</td>
252
+ <td>30.88</td><td>52.32</td><td>51.43</td><td>25.07</td><td>27.22</td>
253
+ </tr>
254
+ <tr>
255
+ <td><a href="https://huggingface.co/meta-llama/Meta-Llama-3.1-8B-Instruct" target="_blank">Llama-3.1-8B-Instruct</a></td>
256
+ <td>37.62</td>
257
+ <td>31.77</td><td>53.30</td><td>50.24</td><td>24.48</td><td>28.33</td>
258
+ </tr>
259
+ <tr>
260
+ <td><a href="https://huggingface.co/FreedomIntelligence/AceGPT-v2-8B-chat" target="_blank">AceGPT-v2-8b-chat</a></td>
261
+ <td>38.77</td>
262
+ <td>33.16</td><td>53.80</td><td>50.24</td><td>26.07</td><td>30.56</td>
263
+ </tr>
264
+ <tr>
265
+ <td><a href="https://huggingface.co/google/gemma-2-9b-it" target="_blank">gemma-2-9b-it</a></td>
266
+ <td>38.70</td>
267
+ <td>33.75</td><td>53.69</td><td>50.79</td><td>26.66</td><td>28.61</td>
268
+ </tr>
269
+ <tr>
270
+ <td><a href="https://huggingface.co/google/gemma-3-12b-it" target="_blank">gemma-3-12b-it</a></td>
271
+ <td>41.63</td>
272
+ <td>37.52</td><td>53.14</td><td>51.19</td><td>31.02</td><td>35.28</td>
273
+ </tr>
274
+ <tr>
275
+ <td><a href="https://huggingface.co/inceptionai/jais-family-13b-chat" target="_blank">jais-family-13b-chat</a></td>
276
+ <td>36.96</td>
277
+ <td>30.46</td><td>53.09</td><td>48.18</td><td>25.28</td><td>27.78</td>
278
+ </tr>
279
+ <tr>
280
+ <td><a href="https://huggingface.co/inceptionai/jais-adapted-13b-chat" target="_blank">jais-adapted-13b-chat</a></td>
281
+ <td>36.98</td>
282
+ <td>31.14</td><td>52.87</td><td>50.79</td><td>23.98</td><td>26.11</td>
283
+ </tr>
284
+ <tr>
285
+ <td><a href="https://huggingface.co/Qwen/Qwen2.5-14B-Instruct" target="_blank">Qwen2.5-14B-Instruct</a></td>
286
+ <td>39.48</td>
287
+ <td>33.49</td><td>52.87</td><td>53.41</td><td>27.35</td><td>30.28</td>
288
+ </tr>
289
+ <tr style="border-top: 4px solid;"></tr>
290
+ <tr>
291
+ <td><a href="https://huggingface.co/MBZUAI-Paris/Nile-Chat-4B" target="_blank"><strong>Nile-Chat-4B</strong></a></td>
292
+ <td>51.38</td>
293
+ <td>50.55</td><td>65.32</td><td>60.62</td><td>37.36</td><td>43.06</td>
294
+ </tr>
295
+ <tr>
296
+ <td><a href="https://huggingface.co/MBZUAI-Paris/Nile-Chat-12B" target="_blank"><strong>Nile-Chat-12B</strong></a></td>
297
+ <td>53.88</td>
298
+ <td>53.71</td><td>65.10</td><td>59.98</td><td>41.72</td><td>48.89</td>
299
+ </tr>
300
+ </tbody>
301
+ </table>
302
+
303
+ ### Translation and Transliteration Tasks:
304
  <table>
305
  <tr>
306
  <td rowspan="2">Model</td>
 
505
 
506
  </table>
507
 
508
+
509
  ## Usage and Limitations
510
 
511
  These models have certain limitations that users should be aware of.
 
592
  (Personally Identifiable Information). Developers are encouraged to adhere to
593
  privacy regulations with privacy-preserving techniques.
594
 
595
+ </details>