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app.py

@@ -35,7 +35,6 @@ def _load_model():
     if _tokenizer is None or _model is None:
         _tokenizer = AutoTokenizer.from_pretrained(MODEL_ID, cache_dir=CACHE_DIR)
         _model = AutoModelForSequenceClassification.from_pretrained(MODEL_ID, cache_dir=CACHE_DIR)
-        _model.eval()
         # Warm-up
         with torch.no_grad():
             _ = _model(**_tokenizer(["warm up"], return_tensors="pt")).logits