import gradio as gr from transformers import DistilGPT2LMHeadModel, DistilGPT2Tokenizer # Load pre-trained DistilGPT-2 model and tokenizer tokenizer = DistilGPT2Tokenizer.from_pretrained("distilgpt2") model = DistilGPT2LMHeadModel.from_pretrained("distilgpt2") # Function to generate keywords from input text def generate_keywords(prompt): # Encode the input text inputs = tokenizer.encode(prompt, return_tensors="pt") # Generate output outputs = model.generate(inputs, max_length=50, num_return_sequences=1, no_repeat_ngram_size=2, top_k=50, top_p=0.95) # Decode and return the generated text (keywords) keywords = tokenizer.decode(outputs[0], skip_special_tokens=True) return keywords.strip() # Gradio interface iface = gr.Interface(fn=generate_keywords, inputs=gr.Textbox(label="Enter Ad Prompt", placeholder="E.g., Generate ad keywords for wireless headphones"), outputs=gr.Textbox(label="Generated Keywords"), live=True) # Launch the Gradio interface iface.launch()