Create app.py

app.py

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+import gradio as gr
+import torch
+from transformers import AutoModelForCausalLM, AutoTokenizer
+
+# Load the model and tokenizer
+MODEL_NAME = "ubiodee/Cardano_plutus"  # Your fine-tuned model
+tokenizer = AutoTokenizer.from_pretrained(MODEL_NAME)
+model = AutoModelForCausalLM.from_pretrained(MODEL_NAME)
+
+# Function to generate response from the model
+def generate_response(prompt):
+    inputs = tokenizer(prompt, return_tensors="pt")
+    with torch.no_grad():
+        output = model.generate(**inputs, max_length=512)
+    response = tokenizer.decode(output[0], skip_special_tokens=True)
+    return response
+
+# Gradio Interface
+iface = gr.Interface(
+    fn=generate_response,
+    inputs=gr.Textbox(label="Enter your prompt"),
+    outputs=gr.Textbox(label="Model Response"),
+    title="Cardano Plutus AI",
+    description="Type in your question or prompt related to Cardano Plutus and get a response from the AI model.",
+    theme="default"
+)
+
+# Launch app
+iface.launch()