Update README.md

README.md

@@ -10,22 +10,28 @@ PS : the tokenizer is the same as the one of the model bert-base-uncased.
 To load the model \& tokenizer :
 
 ````python
-from transformers import AutoModelForMaskdLM, AutoTokenizer
+from transformers import BertForMaskedLM, BertTokenizer
 
 model_name = "eli4s/Bert-L12-h384-A6"
-model = AutoModelForMaskedLM.from_pretrained(model_name)
-tokenizer = AutoTokenizer.from_pretrained(model_name)
+model = BertForMaskedLM.from_pretrained(model_name)
+tokenizer = BertTokenizer.from_pretrained(model_name)
 ````
 
 To use it on a sentence :
 
 ````python
-encoded_inputs = tokenizer(['Paris is the [MASK] of France.'], padding='longest')
+import torch
+
+sentence = "The goal of life is [MASK]."
+
+encoded_inputs = tokenizer([sentence], padding='longest')
 input_ids = torch.tensor(encoded_inputs['input_ids'])
 attention_mask = torch.tensor(encoded_inputs['attention_mask'])
 output = model(input_ids, attention_mask=attention_mask)
 
 mask_index = input_ids.tolist()[0].index(103)
 masked_token = output['logits'][0][mask_index].argmax(axis=-1)
-tokenizer.decode(masked_token)
+predicted_token = tokenizer.decode(masked_token)
+
+print(predicted_token)
 ````