| import gradio as gr | |
| from transformers import AutoModelWithLMHead, AutoTokenizer | |
| model_name = "distilbert-base-uncased" | |
| model = AutoModelWithLMHead.from_pretrained(model_name) | |
| tokenizer = AutoTokenizer.from_pretrained(model_name) | |
| def complete_sentence(sentence): | |
| input_ids = tokenizer.encode(sentence, return_tensors="pt") | |
| output = model.generate(input_ids, max_length=50, num_return_sequences=1) | |
| completed_sentence = tokenizer.decode(output[0], skip_special_tokens=True) | |
| return completed_sentence | |
| iface = gr.Interface(fn=complete_sentence, inputs="text", outputs="text") | |
| if __name__ == "__main__": | |
| iface.launch() | |