fix example code (#2)

- fix example code (606df5fa509bfdd6b8800b7a72bd2c63403dccf1)


Co-authored-by: Peter Szemraj <[email protected]>

README.md

@@ -19,18 +19,19 @@ from transformers import AutoTokenizer, AutoModelForSequenceClassification
 tokenizer = AutoTokenizer.from_pretrained("HuggingFaceTB/fineweb-edu-classifier")
 model = AutoModelForSequenceClassification.from_pretrained("HuggingFaceTB/fineweb-edu-classifier")
 
-inputs = tokenizer("Your text here", return_tensors="pt", padding="longest", truncation=True)
-inputs = tokenizer(texts, return_tensors="pt", padding="longest", truncation=True).
+text = "This is a test sentence."
+inputs = tokenizer(text, return_tensors="pt", padding="longest", truncation=True)
 outputs = model(**inputs)
-logits = outputs.logits.squeeze(-1).float().numpy()
+logits = outputs.logits.squeeze(-1).float().detach().numpy()
 score = logits.item()
 result = {
     "text": text,
     "score": score,
-    "int_score": int(round(max(0, min(score, 5))))
+    "int_score": int(round(max(0, min(score, 5)))),
 }
 
 print(result)
+# {'text': 'This is a test sentence.', 'score': 0.07964489609003067, 'int_score': 0}
 ```
 
 ## Training