Update app.py

app.py

@@ -1,25 +1,26 @@
 import gradio as gr
-from transformers import AutoTokenizer, AutoModelForCausalLM
+from huggingface_hub import InferenceClient
 
-# Load your model
-model_name = "loocorez/reverse-text-warmup"
-tokenizer = AutoTokenizer.from_pretrained(model_name)
-model = AutoModelForCausalLM.from_pretrained(model_name)
+# Use Inference API instead of loading model locally
+client = InferenceClient("loocorez/reverse-text-warmup")
 
 def reverse_text(input_text):
-    # Add your model inference logic here
-    inputs = tokenizer(input_text, return_tensors="pt")
-    outputs = model.generate(**inputs, max_length=100)
-    result = tokenizer.decode(outputs[0], skip_special_tokens=True)
-    return result
+    try:
+        # Use the inference API
+        response = client.text_generation(
+            input_text,
+            max_new_tokens=100,
+            temperature=0.7
+        )
+        return response
+    except Exception as e:
+        return f"Error: {str(e)}"
 
-# Create Gradio interface
 demo = gr.Interface(
     fn=reverse_text,
     inputs=gr.Textbox(label="Input Text"),
-    outputs=gr.Textbox(label="Reversed Text"),
-    title="Reverse Text Model Demo",
-    description="Test the reverse-text-warmup model"
+    outputs=gr.Textbox(label="Output"),
+    title="Reverse Text Model Demo"
 )
 
 demo.launch()