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| import gradio as gr | |
| from huggingface_hub import InferenceClient | |
| # Initialize the Hugging Face Inference client | |
| client = InferenceClient() | |
| def generate_text(prompt): | |
| try: | |
| # Generate text using the Inference API | |
| generated_text = client.text_generation( | |
| prompt, | |
| model="HuggingFaceTB/SmolLM2-1.7B-Instruct", | |
| max_new_tokens=200, | |
| do_sample=True, | |
| temperature=0.7 | |
| ) | |
| return generated_text | |
| except Exception as e: | |
| return f"Error generating text: {str(e)}" | |
| # Create the Gradio interface with modern theme | |
| with gr.Blocks() as demo: | |
| gr.Markdown("# SmolLM Text Generation 🚀") | |
| gr.Markdown("Built with [anycoder](https://huggingface.co/spaces/akhaliq/anycoder)") | |
| with gr.Row(): | |
| with gr.Column(): | |
| input_text = gr.Textbox( | |
| label="Input Prompt", | |
| placeholder="Enter your prompt here...", | |
| lines=5 | |
| ) | |
| generate_btn = gr.Button("Generate", variant="primary") | |
| with gr.Column(): | |
| output_text = gr.Textbox( | |
| label="Generated Text", | |
| interactive=False, | |
| lines=10 | |
| ) | |
| # Add examples | |
| examples = [ | |
| ["Explain quantum computing in simple terms"], | |
| ["Write a short story about a robot learning to love"], | |
| ["How do I make a perfect omelette?"] | |
| ] | |
| gr.Examples( | |
| examples=examples, | |
| inputs=input_text, | |
| outputs=output_text, | |
| fn=generate_text, | |
| cache_examples=True | |
| ) | |
| generate_btn.click( | |
| fn=generate_text, | |
| inputs=input_text, | |
| outputs=output_text, | |
| api_visibility="public" | |
| ) | |
| # Launch with modern theme and settings | |
| demo.launch( | |
| theme=gr.themes.Soft(primary_hue="blue"), | |
| footer_links=[ | |
| {"label": "Built with anycoder", "url": "https://huggingface.co/spaces/akhaliq/anycoder"}, | |
| {"label": "Model", "url": "https://huggingface.co/HuggingFaceTB/SmolLM2-1.7B-Instruct"} | |
| ] | |
| ) |