| from transformers import GPT2LMHeadModel,GPT2Tokenizer | |
| import gradio as grad | |
| mdl = GPT2LMHeadModel.from_pretrained('gpt2') | |
| gpt2_tkn=GPT2Tokenizer.from_pretrained('gpt2') | |
| def generate(starting_text): | |
| tkn_ids = gpt2_tkn.encode(starting_text, return_tensors = 'pt') | |
| gpt2_tensors = mdl.generate(tkn_ids) | |
| response = gpt2_tensors | |
| return response | |
| txt=grad.Textbox(lines=1, label="English", placeholder="English Text here") | |
| out=grad.Textbox(lines=1, label="Generated Tensors") | |
| grad.Interface(generate, inputs=txt, outputs=out).launch() | |