Update README.md

README.md

@@ -21,6 +21,8 @@ tokenizer = AutoTokenizer.from_pretrained("Voicelab/herbert-base-cased-sentiment
 
 model = AutoModelForSequenceClassification.from_pretrained("Voicelab/herbert-base-cased-sentiment")
 
+input = ["Ale fajnie, spadł dzisiaj śnieg! Ulepimy dziś bałwana?"]
+
 encoding = tokenizer(
           input,
           add_special_tokens=True,
@@ -29,9 +31,10 @@ encoding = tokenizer(
           padding='max_length',
           return_attention_mask=True,
           return_tensors='pt',
-        ).to("cuda:0")
+        )
 output = model(**encoding).logits.to("cpu").detach().numpy()
 prediction = id2label[np.argmax(output)]
+print(input, "--->", prediction)
 
 ```