Update app.py

app.py

@@ -1,27 +1,25 @@
 import gradio as gr
-from huggingface_hub import InferenceClient
-import os
+from transformers import AutoTokenizer, AutoModelForCausalLM
 
-token = os.getenv("HF_TOKEN")
-client = InferenceClient("loocorez/reverse-text-warmup", token=token)
+# Load your model
+model_name = "loocorez/reverse-text-warmup"
+tokenizer = AutoTokenizer.from_pretrained(model_name)
+model = AutoModelForCausalLM.from_pretrained(model_name)
 
 def reverse_text(input_text):
-    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)}"
+    # 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
 
+# Create Gradio interface
 demo = gr.Interface(
     fn=reverse_text,
     inputs=gr.Textbox(label="Input Text"),
-    outputs=gr.Textbox(label="Output"),
-    title="Reverse Text Model Demo"
+    outputs=gr.Textbox(label="Reversed Text"),
+    title="Reverse Text Model Demo",
+    description="Test the reverse-text-warmup model"
 )
 
 demo.launch()