Update README.md

README.md

@@ -64,8 +64,33 @@ tokenizer = AutoTokenizer.from_pretrained('DeepNeural/ner_classifier_v2')
 model = AutoModelForTokenClassification.from_pretrained('DeepNeural/ner_classifier_v2')
 
 ```
+### Making predictions
 
+1. Preparing the model 
+```python
+#Creating an easy tags function
+#Custom configured model needs improvement, let's train it
+def tag_text(text, tags, model, tokenizer) -> pd.DataFrame:
+    #Get tokens with special characters
+    tokens = tokenizer(text).tokens()
+    #Encode the sequence into IDs
+    input_ids = tokenizer(text, return_tensors="pt").input_ids.to(device)
+    #Get predictions as a distribution over 7 classes
+    outputs = model(input_ids)[0]
+    #Take argmax to get most likely class per token
+    predictions = torch.argmax(outputs, dim=2)
+    #Convert to DataFrame
+    preds = [ner_tags.names[p] for p in predictions[0].cpu().numpy()]
+    return pd.DataFrame([tokens, preds], index=["Tokens", "Tags"])
+
+```
 
+2. Example for making predictions
+   ```python
+     #Testing the model
+      dummy_text = "DeepNeural is an organization seeking to revolutionize healthcare"
+      tag_text(dummy_text, ner_tags, trainer.model, tokenizer)
+   ```
 ### Framework versions
 
 - Transformers 4.56.2