Update README.md

README.md

@@ -1,6 +1,8 @@
 ---
 library_name: transformers
 license: apache-2.0
+base_model:
+- BSC-LT/MrBERT
 ---
 
 # JaunBERT
@@ -26,26 +28,26 @@ You can either use this model directly as the example below, or fine-tune it to
 >>> pipe = pipeline("fill-mask", model='HiTZ/JaunBERT')
 
 >>> pipe("Kaixo! Ni <mask> naiz!")
-[{'score': 0.022003261372447014,
-  'token': 7497,
-  'token_str': ' euskalduna',
-  'sequence': 'Kaixo! Ni euskalduna naiz!'},
- {'score': 0.016429167240858078,
-  'token': 14067,
-  'token_str': ' Olentzero',
-  'sequence': 'Kaixo! Ni Olentzero naiz!'},
- {'score': 0.012804778292775154,
-  'token': 31087,
-  'token_str': ' ahobizi',
-  'sequence': 'Kaixo! Ni ahobizi naiz!'},
- {'score': 0.01173020526766777,
-  'token': 331,
-  'token_str': ' ez',
-  'sequence': 'Kaixo! Ni ez naiz!'},
- {'score': 0.010091394186019897,
-  'token': 7618,
-  'token_str': ' irakaslea',
-  'sequence': 'Kaixo! Ni irakaslea naiz!'}]
+[{'score': 0.034423828125,
+  'token': 71333,
+  'token_str': 'Aitor',
+  'sequence': 'Kaixo! Ni Aitor  naiz!'},
+ {'score': 0.032470703125,
+  'token': 119830,
+  'token_str': 'Asier',
+  'sequence': 'Kaixo! Ni Asier  naiz!'},
+ {'score': 0.0208740234375,
+  'token': 109222,
+  'token_str': 'Unai',
+  'sequence': 'Kaixo! Ni Unai  naiz!'},
+ {'score': 0.0196533203125,
+  'token': 164657,
+  'token_str': 'Nerea',
+  'sequence': 'Kaixo! Ni Nerea  naiz!'},
+ {'score': 0.0196533203125,
+  'token': 40163,
+  'token_str': 'Ane',
+  'sequence': 'Kaixo! Ni Ane  naiz!'}]
 ```
 
 ## Training Data