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app.py

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+import gradio as gr
+from transformers import pipeline
+
+# Load text generation pipeline
+generator = pipeline("text-generation", model="gpt2")
+
+def generate_text(prompt, max_length=100, temperature=0.7):
+    result = generator(
+        prompt,
+        max_length=max_length,
+        num_return_sequences=1,
+        temperature=temperature,
+        pad_token_id=50256  # for GPT2 to avoid warnings
+    )
+    return result[0]['generated_text']
+
+with gr.Blocks() as demo:
+    gr.Markdown("## Text Generation App (GPT-2 Demo)")
+
+    prompt = gr.Textbox(
+        lines=3, 
+        placeholder="Enter a starting sentence...",
+        label="Prompt"
+    )
+    length = gr.Slider(50, 300, value=100, step=10, label="Max Length")
+    temp = gr.Slider(0.1, 1.0, value=0.7, step=0.1, label="Creativity (Temperature)")
+    output = gr.Textbox(lines=10, label="Generated Text")
+
+    btn = gr.Button("Generate")
+    btn.click(fn=generate_text, inputs=[prompt, length, temp], outputs=output)
+
+demo.launch()

requirements.txt

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+gradio>=3.30
+transformers>=4.40
+torch>=1.13