Update app.py

app.py

@@ -77,9 +77,9 @@ model_g = Qwen2_5_VLForConditionalGeneration.from_pretrained(
     MODEL_ID_G, trust_remote_code=True, subfolder=SUBFOLDER, torch_dtype=torch.float16
 ).to(device).eval()
 
-MODEL_ID_I = "google/gemma-3-4b-it"
+MODEL_ID_I = "HuggingFaceTB/SmolVLM2-2.2B-Instruct"
 processor_i = AutoProcessor.from_pretrained(MODEL_ID_I, trust_remote_code=True)
-model_i = Gemma3ForConditionalGeneration.from_pretrained(
+model_i = AutoModelForImageTextToText.from_pretrained(
     MODEL_ID_I, trust_remote_code=True, torch_dtype=torch.float16, _attn_implementation="flash_attention_2"
 ).to(device).eval()
 
@@ -178,7 +178,7 @@ def process_document_stream(
     elif model_name == "LFM2-VL-1.6B": processor, model = processor_t, model_t
     elif model_name == "SmolVLM-Instruct-250M": processor, model = processor_c, model_c
     elif model_name == "MonkeyOCR-pro-1.2B": processor, model = processor_g, model_g
-    elif model_name == "gemma-3-4b-it": processor, model = processor_i, model_i
+    elif model_name == "SmolVLM2-2.2B-Instruct": processor, model = processor_i, model_i
     else:
         yield "Invalid model selected.", ""
         return
@@ -235,7 +235,7 @@ def create_gradio_interface():
             # Left Column (Inputs)
             with gr.Column(scale=1):
                 model_choice = gr.Dropdown(
-                    choices=["LFM2-VL-1.6B", "LFM2-VL-450M", "SmolVLM-Instruct-250M", "gemma-3-4b-it", "MonkeyOCR-pro-1.2B"],
+                    choices=["LFM2-VL-1.6B", "LFM2-VL-450M", "SmolVLM-Instruct-250M", "SmolVLM2-2.2B-Instruct", "MonkeyOCR-pro-1.2B"],
                     label="Select Model", value="LFM2-VL-1.6B"
                 )
                 prompt_input = gr.Textbox(label="Query Input", placeholder="✦︎ Enter your query")