Upload models

app.py

@@ -96,8 +96,14 @@ EMBEDDINGS_PATH = "embeddings_file.npy"
 # Load generator model (T5)
 @st.cache_resource
 def load_llm():
-    tokenizer = T5Tokenizer.from_pretrained("Ah1111/Generator_Model")
-    model = T5ForConditionalGeneration.from_pretrained("Ah1111/Generator_Model")
+    # tokenizer = T5Tokenizer.from_pretrained("Ah1111/Generator_Model")
+    # model = T5ForConditionalGeneration.from_pretrained("Ah1111/Generator_Model")
+    # return tokenizer, model
+
+    model_name = "google/flan-t5-base"
+
+    tokenizer = AutoTokenizer.from_pretrained(model_name)
+    model = AutoModelForSeq2SeqLM.from_pretrained(model_name)
     return tokenizer, model
 
 # Load embedding model (custom Hugging Face model)