Create app.py

app.py

@@ -0,0 +1,29 @@
+import torch
+from transformers import AutoModelForCausalLM, AutoTokenizer, pipeline
+import gradio as gr
+
+# Load GPT-2 XL model
+model_name = "gpt2-xl"
+tokenizer = AutoTokenizer.from_pretrained(model_name)
+model = AutoModelForCausalLM.from_pretrained(model_name)
+
+# Create generator pipeline
+generator = pipeline('text-generation', model=model, tokenizer=tokenizer)
+
+def generate_data(prompt, amount):
+    responses = []
+    for _ in range(amount):
+        output = generator(prompt, max_length=100, num_return_sequences=1)[0]['generated_text']
+        responses.append(output.strip())
+    return responses
+
+with gr.Blocks() as demo:
+    gr.Markdown("### GPT-2 XL Data Generator\nDescribe the data you'd like the AI to generate.")
+    prompt_input = gr.Textbox(label="Prompt / Data Type", placeholder="Describe the data you want")
+    amount_input = gr.Slider(1, 10, value=3, step=1, label="Number of Data Items")
+    output_box = gr.Textbox(label="Generated Data", lines=15)
+
+    generate_btn = gr.Button("Generate")
+    generate_btn.click(generate_data, inputs=[prompt_input, amount_input], outputs=output_box)
+
+demo.launch()