use top_k instead of return_all_scores

README.md

@@ -24,7 +24,7 @@ pipe = opt_pipeline(
     function_to_apply="sigmoid",
     accelerator="ort",
     tokenizer=tokenizer,
-    return_all_scores=True,  # return scores for all the labels, model was trained as multilabel
+    top_k=None,  # return scores for all the labels, model was trained as multilabel
 )
 
 print(pipe(['example text','exemple de texte','texto de ejemplo','testo di esempio','texto de exemplo','örnek metin','пример текста']))