Update README.md

README.md

@@ -39,19 +39,19 @@ For more detailed code regarding generating the annotations in Toxic Commons, tr
 
 ```
 from transformers import AutoTokenizer
-from model import MultiHeadDebertaForSequenceClassification
+from celadon.model import MultiHeadDebertaForSequenceClassification
 
-tokenizer = AutoTokenizer.from_pretrained("PleIAs/celadon")
-model = MultiHeadDebertaForSequenceClassification.from_pretrained("PleIAs/celadon")
+tokenizer = AutoTokenizer.from_pretrained("celadon")
+model = MultiHeadDebertaForSequenceClassification.from_pretrained("celadon")
 model.eval()
 
 sample_text = "This is an example of a normal sentence"
 
 inputs = tokenizer(sample_text, return_tensors="pt", padding=True, truncation=True)
-outputs = model(**inputs)
+outputs = model(input_ids=inputs['input_ids'], attention_mask=inputs['attention_mask'])
 
 categories = ['Race/Origin', 'Gender/Sex', 'Religion', 'Ability', 'Violence']
-predictions = outputs.argmax(dim=-1).squeeze().tolist()[0]  
+predictions = outputs.argmax(dim=-1).squeeze().tolist()
 
 # Print the classification results for each category
 print(f"Text: {sample_text}")