Update src/streamlit_app.py

add model and tokenizer to NER pipeline

src/streamlit_app.py

@@ -570,7 +570,23 @@ def load_financial_models():
         finbert_model = AutoModelForSequenceClassification.from_pretrained("yiyanghkust/finbert-tone", cache_dir=cache_dir)
         
         # Financial NER for entity extraction
-        ner_pipeline = pipeline("ner", model="elastic/distilbert-base-cased-finetuned-conll03-english", aggregation_strategy="simple", cache_dir=cache_dir)
+        #ner_pipeline = pipeline("ner", model="elastic/distilbert-base-cased-finetuned-conll03-english", aggregation_strategy="simple", cache_dir=cache_dir)
+        
+        # Load Financial NER model and tokenizer explicitly
+        ner_tokenizer = AutoTokenizer.from_pretrained(
+            "elastic/distilbert-base-cased-finetuned-conll03-english", cache_dir=cache_dir
+        )
+        ner_model = AutoModelForTokenClassification.from_pretrained(
+            "elastic/distilbert-base-cased-finetuned-conll03-english", cache_dir=cache_dir
+        )
+
+        # Then create pipeline using objects
+        ner_pipeline = pipeline(
+            "ner",
+            model=ner_model,
+            tokenizer=ner_tokenizer,
+            aggregation_strategy="simple",
+        )
         
         return finbert_tokenizer, finbert_model, ner_pipeline, None
     except Exception as e: