Update README.md

README.md

@@ -8,7 +8,7 @@ tags: ['bart-base','sentiment classification','tweeter','binary classification']
 <!-- Provide a quick summary of what the model is/does. -->
 This is a fine-tune of `bart-base` to a sentiment classification dataset. 
 
-```
+```python
 
 from transformers import BartTokenizer, AutoModelForSequenceClassification
 model = AutoModelForSequenceClassification.from_pretrained('mylonasc/bart-base-twitter-sent-ft-001')
@@ -18,13 +18,16 @@ _phrases = [
     'this is a great model! I really like it!', 
     'Do you call this a model? This is not even 1B parameters! Get outta here!',
     'Fine tuning transformers is very easy if you use all the right tools!',
-    "John doesnt know how to code to save his life..."
+    "John couldn't write two correct lines of code without ChatGPT if his life depended on it..."
 ]
 toks = tokenizer(_phrases, return_tensors='pt', padding = 'longest')
 with torch.no_grad():
     res = model(**toks)[0]
 is_positive = res.softmax(1)[:,1]
 is_positive
+
+
+>> tensor([0.9994, 0.1362, 0.9995, 0.3840])
 ```
 
 ## Model Details