Update app.py

app.py

@@ -1,15 +1,6 @@
 from transformers import AutoTokenizer, AutoModel
 
-# Laden des SciBERT-Modells
-tokenizer = AutoTokenizer.from_pretrained('allenai/scibert_scivocab_uncased')
-model = AutoModel.from_pretrained('allenai/scibert_scivocab_uncased')
-
-# Beispiel-Text
-text = "This paper introduces a novel deep learning approach for cancer diagnosis."
-
-# Tokenisierung & Modell-Durchlauf
-inputs = tokenizer(text, return_tensors="pt")  # Falls du TensorFlow nutzt: return_tensors="tf"
-outputs = model(**inputs)
-
-# Anzeigen der Ausgabe
-print(outputs.last_hidden_state.shape)
+# Explizite Angabe von torch_dtype kann helfen
+model_name = "allenai/scibert_scivocab_uncased"
+tokenizer = AutoTokenizer.from_pretrained(model_name)
+model = AutoModel.from_pretrained(model_name, torch_dtype=torch.float32)