Update README.md

README.md

@@ -542,8 +542,8 @@ Use the code below to get started with the model.
 ```python
 from transformers import AutoTokenizer, AutoModelForCausalLM
 
-tokenizer = AutoTokenizer.from_pretrained("OpenLLM-Ro/RoLlama2-7b-Instruct")
-model = AutoModelForCausalLM.from_pretrained("OpenLLM-Ro/RoLlama2-7b-Instruct")
+tokenizer = AutoTokenizer.from_pretrained("OpenLLM-Ro/RoLlama2-7b-Instruct-2024-10-09")
+model = AutoModelForCausalLM.from_pretrained("OpenLLM-Ro/RoLlama2-7b-Instruct-2024-10-09")
 
 instruction = "Care este cel mai înalt vârf muntos din România?"
 chat = [
@@ -578,16 +578,18 @@ print(tokenizer.decode(outputs[0]))
 <td>RoLlama2-7b-Instruct-2024-05-14</td><td><center><strong>45.71</strong></center></td><td><center>43.66</center></td><td><center>39.70</center></td><td><center><strong>70.34</strong></center></td><td><center>57.36</center></td><td><center><strong>18.78</strong></center></td><td><center>44.44</center></td>
 </tr>
 <tr>
-<td><em>RoLlama2-7b-Instruct-2024-10-09</em></td><td><center><em>44.50</em></center></td><td><center><em><strong>44.73</strong></em></center></td><td><center><em><strong>40.39</strong></em></center></td><td><center><em>63.67</em></center></td><td><center><em><strong>59.12</strong></em></center></td><td><center><em>13.29</em></center></td><td><center><em><strong>45.78</strong></em></center></td>
+<td><em>RoLlama2-7b-Instruct-2024-10-09</em></td><td><center><em>44.50</em></center></td><td><center><em><strong>44.73</strong></em></center></td><td><center><em><strong>40.39</strong></em></center></td><td><center><em>63.67</em></center></td><td><center><em>59.12</em></center></td><td><center><em>13.29</em></center></td><td><center><em><strong>45.78</strong></em></center></td>
+</tr>
+<tr>
+<td>RoLlama2-7b-Instruct-DPO-2024-10-09</td><td><center>43.20</center></td><td><center>44.24</center></td><td><center>38.39</center></td><td><center>62.57</center></td><td><center><strong>59.20</strong></center></td><td><center>15.72</center></td><td><center>39.07</center></td>
 </tr>
 </tbody>
 </table>
 
-
 ## Downstream tasks
 
                                   
-<table>
+v<table>
 <tbody>
 <tr>
 <td></td>
@@ -621,6 +623,9 @@ print(tokenizer.decode(outputs[0]))
 <tr>
 <td><em>RoLlama2-7b-Instruct-2024-10-09</em></td><td><center><em><strong>97.66</strong></em></center></td><td><center><em>62.41</em></center></td><td><center><em>97.97</em></center></td><td><center><em>60.89</em></center></td><td><center><em>27.13</em></center></td><td><center><em>19.39</em></center></td><td><center><em><strong>27.63</strong></em></center></td><td><center><em>39.75</em></center></td>
 </tr>
+<tr>
+<td>RoLlama2-7b-Instruct-DPO-2024-10-09</td><td><center>97.31</center></td><td><center>60.56</center></td><td><center>-</center></td><td><center>-</center></td><td><center>26.56</center></td><td><center>21.68</center></td><td><center>-</center></td><td><center>-</center></td>
+</tr>
 </tbody>
 </table>
 
@@ -659,9 +664,13 @@ print(tokenizer.decode(outputs[0]))
 <tr>
 <td><em>RoLlama2-7b-Instruct-2024-10-09</em></td><td><center><em><strong>45.71</strong></em></center></td><td><center><em><strong>65.08</strong></em></center></td><td><center><em>59.24</em></center></td><td><center><em>74.25</em></center></td><td><center><em>59.69</em></center></td><td><center><em>57.16</em></center></td><td><center><em><strong>84.66</strong></em></center></td><td><center><em><strong>85.07</strong></em></center></td>
 </tr>
+<tr>
+<td>RoLlama2-7b-Instruct-DPO-2024-10-09</td><td><center>35.78</center></td><td><center>59.31</center></td><td><center>-</center></td><td><center>-</center></td><td><center>61.22</center></td><td><center>58.41</center></td><td><center>-</center></td><td><center>-</center></td>
+</tr>
 </tbody>
 </table>
 
+
 ## Romanian MT-Bench
 
 <table>
@@ -680,13 +689,15 @@ print(tokenizer.decode(outputs[0]))
 <td>RoLlama2-7b-Instruct-2024-05-14</td><td><center>3.86</center></td><td><center>4.67</center></td><td><center>3.04</center></td><td><center><strong>160/160</strong></center></td>
 </tr>
 <tr>
-<td><em>RoLlama2-7b-Instruct-2024-10-09</em></td><td><center><em><strong>4.43</strong></em></center></td><td><center><em><strong>4.92</strong></em></center></td><td><center><em><strong>3.94</strong></em></center></td><td><center><em><strong>160/160</strong></em></center></td>
+<td><em>RoLlama2-7b-Instruct-2024-10-09</em></td><td><center><em>4.43</em></center></td><td><center><em>4.92</em></center></td><td><center><em>3.94</em></center></td><td><center><em><strong>160/160</strong></em></center></td>
+</tr>
+<tr>
+<td>RoLlama2-7b-Instruct-DPO-2024-10-09</td><td><center><strong>4.61</strong></center></td><td><center><strong>5.15</strong></center></td><td><center><strong>4.06</strong></center></td><td><center><strong>160/160</strong></center></td>
 </tr>
 </tbody>
 </table>
 
 
-
 ## RoCulturaBench
 
 
@@ -704,7 +715,10 @@ print(tokenizer.decode(outputs[0]))
 <td>RoLlama2-7b-Instruct-2024-05-14</td><td><center>3.77</center></td><td><center><strong>100/100</strong></center></td>
 </tr>
 <tr>
-<td><em>RoLlama2-7b-Instruct-2024-10-09</em></td><td><center><em><strong>4.08</strong></em></center></td><td><center><em><strong>100/100</strong></em></center></td>
+<td><em>RoLlama2-7b-Instruct-2024-10-09</em></td><td><center><em>4.08</em></center></td><td><center><em><strong>100/100</strong></em></center></td>
+</tr>
+<tr>
+<td>RoLlama2-7b-Instruct-DPO-2024-10-09</td><td><center><strong>4.80</strong></center></td><td><center><strong>100/100</strong></center></td>
 </tr>
 </tbody>
 </table>
@@ -712,6 +726,7 @@ print(tokenizer.decode(outputs[0]))
 
 
 
+
 ## RoLlama2 Model Family
 
 | Model              | Link  |