Update load_model.py

load_model.py

@@ -1,19 +1,19 @@
-from transformers import BertTokenizer, BertForSequenceClassification
-import streamlit as st
-
-# Dictionary to map model names to their paths
-model_paths = {
-    "cahya/bert-base-indonesian-522M": "Nakhwa/cahyabert",
-    "indobenchmark/indobert-base-p2": "Nakhwa/indobenchmark",
-    "indolem/indobert-base-uncased": "Nakhwa/indolem",
-    "mdhugol/indonesia-bert-sentiment-classification": "Nakhwa/mdhugol"
-}
-
-# Function to load the selected model
-@st.cache_resource
-def load_model(model_name):
-    path = model_paths[model_name]
-    tokenizer = BertTokenizer.from_pretrained(path)
-    model = BertForSequenceClassification.from_pretrained(path)
-    model.eval()
-    return tokenizer, model
+from transformers import BertTokenizer, BertForSequenceClassification
+import streamlit as st
+
+# Dictionary to map model names to their paths
+model_paths = {
+    "cahya/bert-base-indonesian-522M": "nlp-brin-id/cahyabert",
+    "indobenchmark/indobert-base-p2": "nlp-brin-id/indobenchmark",
+    "indolem/indobert-base-uncased": "nlp-brin-id/indolem",
+    "mdhugol/indonesia-bert-sentiment-classification": "nlp-brin-id/mdhugol"
+}
+
+# Function to load the selected model
+@st.cache_resource
+def load_model(model_name):
+    path = model_paths[model_name]
+    tokenizer = BertTokenizer.from_pretrained(path)
+    model = BertForSequenceClassification.from_pretrained(path)
+    model.eval()
+    return tokenizer, model