update app

app.py

@@ -18,6 +18,7 @@ import cv2
 from transformers import (
     Qwen2_5_VLForConditionalGeneration,
     Qwen3VLForConditionalGeneration,
+    LightOnOCRForConditionalGeneration,
     AutoModelForImageTextToText,
     AutoModelForCausalLM,
     AutoProcessor,
@@ -177,6 +178,16 @@ model_x = Qwen2_5_VLForConditionalGeneration.from_pretrained(
     torch_dtype=torch.float16
 ).to(device).eval()
 
+# Load LightOnOCR
+MODEL_ID_L = "lightonai/LightOnOCR-1B-1025"
+processor_l = AutoProcessor.from_pretrained(MODEL_ID_L, trust_remote_code=True)
+model_l = LightOnOCRForConditionalGeneration.from_pretrained(
+    MODEL_ID_L,
+    attn_implementation="flash_attention_2",
+    trust_remote_code=True,
+    torch_dtype=torch.float16
+).to(device).eval()
+
 # Load Dots.OCR from the local, patched directory
 MODEL_PATH_D = "strangervisionhf/dots.ocr-base-fix"
 processor_d = AutoProcessor.from_pretrained(MODEL_PATH_D, trust_remote_code=True)
@@ -217,6 +228,9 @@ def generate_image(model_name: str, text: str, image: Image.Image,
     elif model_name == "Dots.OCR":
         processor = processor_d
         model = model_d
+    elif model_name == "LightOnOCR-1B":
+        processor = processor_l
+        model = model_l
     else:
         yield "Invalid model selected.", "Invalid model selected."
         return
@@ -293,7 +307,7 @@ with gr.Blocks(css=css, theme=steel_blue_theme) as demo:
                     markdown_output = gr.Markdown(label="(Result.Md)")
 
                 model_choice = gr.Radio(
-                    choices=["Nanonets-OCR2-3B", "Chandra-OCR", "Dots.OCR", "olmOCR-2-7B-1025"],
+                    choices=["Nanonets-OCR2-3B", "Chandra-OCR", "Dots.OCR", "LightOnOCR-1B", "olmOCR-2-7B-1025"],
                     label="Select Model",
                     value="Nanonets-OCR2-3B"
                 )