Update app_flash.py

app_flash.py

@@ -63,12 +63,20 @@ def build_encoder(model_name="gpt2", max_length: int = 32):
 # 3️⃣ Load pretrained FlashPack model (skip training)
 # ============================================================
 def load_flashpack_model(hf_repo="rahul7star/FlashPack"):
-    print(f"🔁 Loading FlashPack model from: {hf_repo}")
-    model = GemmaTrainer.load_flashpack(hf_repo)
-    model.eval()
-    tokenizer, embed_model, encode_fn = build_encoder("gpt2", max_length=32)
+    model = GemmaTrainer.from_flashpack(hf_repo)
+    tokenizer = model.tokenizer if hasattr(model, "tokenizer") else None
+    embed_model = model.embed_model if hasattr(model, "embed_model") else None
     return model, tokenizer, embed_model
 
+# def load_flashpack_model(hf_repo="rahul7star/FlashPack"):
+#     print(f"🔁 Loading FlashPack model from: {hf_repo}")
+   
+#     model = GemmaTrainer.from_flashpack(hf_repo)
+
+#     model.eval()
+#     tokenizer, embed_model, encode_fn = build_encoder("gpt2", max_length=32)
+#     return model, tokenizer, embed_model
+
 
 # ============================================================
 # 4️⃣ Load Gemma text model for prompt enhancement