Update README.md

README.md

@@ -44,8 +44,8 @@ MODEL_PATH = "helinivan/italian-sarcasm-detector"
 tokenizer = AutoTokenizer.from_pretrained(MODEL_PATH)
 model = AutoModelForSequenceClassification.from_pretrained(MODEL_PATH)
 
-text = "Auto, stop a diesel e benzina dal 2035. Ecco cosa cambia per i consumatori"
-tokenized_text = tokenizer([preprocess_data(text)], padding=True, truncation=True, max_length=512, return_tensors="pt")
+text = "Gli Usa a un passo dalla recessione"
+tokenized_text = tokenizer([preprocess_data(text)], padding=True, truncation=True, max_length=256, return_tensors="pt")
 output = model(**tokenized_text)
 probs = output.logits.softmax(dim=-1).tolist()[0]
 confidence = max(probs)
@@ -57,7 +57,7 @@ results = {"is_sarcastic": prediction, "confidence": confidence}
 Output: 
 
 ```
-{'is_sarcastic': 1, 'confidence': 0.9999909400939941}
+{'is_sarcastic': 0, 'confidence': 0.9965020418167114}
 ```
 
 ## Performance