| import gradio as gr | |
| from transformers import GPT2LMHeadModel, GPT2Tokenizer | |
| model_name = "enzer1992/AI-Guru" | |
| tokenizer = GPT2Tokenizer.from_pretrained(model_name) | |
| model = GPT2LMHeadModel.from_pretrained(model_name) | |
| def generate_text(prompt): | |
| inputs = tokenizer.encode(prompt, return_tensors="pt") | |
| outputs = model.generate(inputs, max_length=100, num_return_sequences=1) | |
| return tokenizer.decode(outputs[0], skip_special_tokens=True) | |
| interface = gr.Interface(fn=generate_text, inputs="text", outputs="text") | |
| interface.launch() | |