Update app.py

app.py

@@ -26,13 +26,8 @@ if not os.path.exists("./models"):
     os.makedirs("./models")
 
 hf_hub_download(
-    repo_id="bartowski/google_gemma-3-1b-it-GGUF",
-    filename="google_gemma-3-1b-it-Q4_K_M.gguf",
-    local_dir="./models",
-)
-hf_hub_download(
-    repo_id="bartowski/google_gemma-3-1b-it-GGUF",
-    filename="google_gemma-3-1b-it-Q5_K_M.gguf",
+    repo_id="SRP-base-model-training/gemma_3_800M_sft_v2_translation-kazparc_latest",
+    filename="gemma_3_800M_sft_v2_translation-kazparc_latest.gguf",
     local_dir="./models",
 )
 
@@ -72,7 +67,7 @@ llm_model = None
 def respond(
     message: str,
     history: List[Tuple[str, str]],
-    model: str = "google_gemma-3-1b-it-Q4_K_M.gguf",  # Set default model
+    model: str = "gemma_3_800M_sft_v2_translation-kazparc_latest.gguf",  # Set default model
     system_message: str = "You are a helpful assistant.",
     max_tokens: int = 1024,
     temperature: float = 0.7,
@@ -102,7 +97,7 @@ def respond(
 
         # Ensure model is not None
         if model is None:
-            model = "google_gemma-3-1b-it-Q4_K_M.gguf"
+            model = "gemma_3_800M_sft_v2_translation-kazparc_latest.gguf"
 
         # Load the model
         if llm is None or llm_model != model:
@@ -184,10 +179,9 @@ demo = gr.ChatInterface(
     additional_inputs=[
         gr.Dropdown(
             choices=[
-                "google_gemma-3-1b-it-Q4_K_M.gguf",
-                "google_gemma-3-1b-it-Q5_K_M.gguf",
+                "gemma_3_800M_sft_v2_translation-kazparc_latest.gguf",
             ],
-            value="google_gemma-3-1b-it-Q4_K_M.gguf",
+            value="gemma_3_800M_sft_v2_translation-kazparc_latest.gguf",
             label="Model",
             info="Select the AI model to use for chat",
         ),