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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() |