| import lib | |
| import nltk, torch | |
| import gradio as gr | |
| from transformers import AutoTokenizer, AutoModelForCausalLM | |
| """ Created by Riky Ripaldo """ | |
| nltk.download('punkt') | |
| tokenz = AutoTokenizer.from_pretrained("microsoft/DialoGPT-medium") | |
| modelz = AutoModelForCausalLM.from_pretrained("microsoft/DialoGPT-medium") | |
| def balasan(chats): | |
| input_ids = tokenz.encode(chats + tokenz.eos_token, return_tensors='pt') | |
| response_ids = modelz.generate(input_ids, max_length=1000, pad_token_id=tokenz.eos_token_id) | |
| response_teks = tokenz.decode(response_ids[0], skip_special_token=True) | |
| return response_teks | |
| gui = gr.Interface( | |
| fn = balasan, | |
| inputs = gr.inputs.Textbox(label="Ketik Pesan"), | |
| outputs = gr.outputs.Textbox(label="Balasan NesiaChan") | |
| ) | |
| gui.launch() |