Upload 2 files

app.py

@@ -0,0 +1,29 @@
+import gradio as gr
+from transformers import AutoProcessor, AutoModel
+
+# Step 1: Load the model and processor
+model_name = "facebook/VFusion3D"
+processor = AutoProcessor.from_pretrained(model_name)
+model = AutoModel.from_pretrained(model_name)
+
+# Step 2: Define the function to process inputs and get predictions
+def predict(input_text):
+    # Convert input into a format the model understands
+    inputs = processor(inputs=input_text, return_tensors="pt")
+    # Get model predictions
+    outputs = model(**inputs)
+    # Return results (adjust based on the model's output format)
+    return outputs.logits.tolist()
+
+# Step 3: Build the Gradio interface
+interface = gr.Interface(
+    fn=predict,
+    inputs="text",  # Change this based on model requirements
+    outputs="text",  # Adjust output format as needed
+    title="VFusion3D Deployment",
+    description="A demo application."
+)
+
+# Step 4: Launch the app
+if __name__ == "__main__":
+    interface.launch()

requirements.txt

@@ -0,0 +1,3 @@
+transformers==4.33.2
+torch==2.0.1
+gradio==3.40.1