Update README.md

README.md

@@ -51,8 +51,25 @@ The largest Spanish biomedical and heath corpus to date gathered from a massive
 WIP 🚧
 
 ## How to use the discriminator in `transformers`
+```py
+from transformers import ElectraForPreTraining, ElectraTokenizerFast
+import torch
 
-TBA
+discriminator = ElectraForPreTraining.from_pretrained("mrm8488/biomedtra-small-es")
+tokenizer = ElectraTokenizerFast.from_pretrained("mrm8488/biomedtra-small-es")
+
+sentence = "Los españoles tienden a sufir déficit de vitamina c"
+fake_sentence = "Los españoles tienden a déficit sufrir de vitamina c"
+
+fake_tokens = tokenizer.tokenize(fake_sentence)
+fake_inputs = tokenizer.encode(fake_sentence, return_tensors="pt")
+discriminator_outputs = discriminator(fake_inputs)
+predictions = torch.round((torch.sign(discriminator_outputs[0]) + 1) / 2)
+
+[print("%7s" % token, end="") for token in fake_tokens]
+
+[print("%7s" % prediction, end="") for prediction in predictions.tolist()]
+```
 
 ## Acknowledgments