Create app.py

app.py

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+import gradio as gr
+from texify.inference import batch_inference
+from texify.model.model import load_model
+from texify.model.processor import load_processor
+from PIL import Image
+
+title="""🙋🏻‍♂️Welcome to🌟Tonic's👨🏻‍🔬Texify"""
+description="""You can upload a picture with a math formula and this model will return latex formulas. Texify is a multimodal input model. You can use this Space to test out the current model [vikp/texify2](https://huggingface.co/vikp/texify2) You can also use  vikp/texify2🚀 by cloning this space.   Simply click here: [Duplicate Space](https://huggingface.co/spaces/Tonic1/texify?duplicate=true)
+Join us:  TeamTonic  is always making cool demos! Join our active builder's community on  Discord: [Discord](https://discord.gg/nXx5wbX9) On  Huggingface: [TeamTonic](https://huggingface.co/TeamTonic) & [MultiTransformer](https://huggingface.co/MultiTransformer) On  Github: [Polytonic](https://github.com/tonic-ai) & contribute to   [PolyGPT](https://github.com/tonic-ai/polygpt-alpha) You can also join the [texify community here](https://discord.gg/zJSDQJWDe8). Big thanks to Vik Paruchuri for the invite and Huggingface for the Community Grant. Your special attentions are much appreciated.
+"""
+
+
+=model = load_model()
+processor = load_processor()
+
+def process_image(img):
+    img = Image.fromarray(img)
+    
+    results = batch_inference([img], model, processor)
+
+    return '\n'.join(results) if isinstance(results, list) else results
+
+iface = gr.Interface(
+    gr.Markdown(title)
+    gr.Markdown(description)
+    fn=process_image,
+    inputs=gr.inputs.Image(type="pil"),
+    outputs="text",
+
+if __name__ == "__main__":
+    iface.launch()