Update README.md

README.md

@@ -6,12 +6,47 @@ datasets:
 ---
 
 ## Model description
+
 CamemBERT is a state-of-the-art language model for French based on the RoBERTa model.
 It is now available on Hugging Face in six different versions with varying number of parameters, amount of pretraining data and pretraining data source domains.
+
 ## Intended uses & limitations
+
 ## How to use
+
+```python
+>>> from transformers import pipeline
+>>> unmasker = pipeline('fill-mask', model='bert-base-cased')
+>>> unmasker("Hello I'm a [MASK] model.")
+
+[{'sequence': "[CLS] Hello I'm a fashion model. [SEP]",
+  'score': 0.09019174426794052,
+  'token': 4633,
+  'token_str': 'fashion'},
+ {'sequence': "[CLS] Hello I'm a new model. [SEP]",
+  'score': 0.06349995732307434,
+  'token': 1207,
+  'token_str': 'new'},
+ {'sequence': "[CLS] Hello I'm a male model. [SEP]",
+  'score': 0.06228214129805565,
+  'token': 2581,
+  'token_str': 'male'},
+ {'sequence': "[CLS] Hello I'm a professional model. [SEP]",
+  'score': 0.0441727414727211,
+  'token': 1848,
+  'token_str': 'professional'},
+ {'sequence': "[CLS] Hello I'm a super model. [SEP]",
+  'score': 0.03326151892542839,
+  'token': 7688,
+  'token_str': 'super'}]
+```
+
 ## Limitations and bias
+
 ## Training data
+
 OSCAR or Open Super-large Crawled Aggregated coRpus is a multilingual corpus obtained by language classification and filtering of the Common Crawl corpus using the Ungoliant architecture.
+
 ## Training procedure
+
 ## Evaluation results