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from transformers import AutoModelForCausalLM, AutoTokenizer, pipeline, AutoModelForQuestionAnswering
import gradio as gr
import torch
title = "🤖AI ChatBot"
description = "A State-of-the-Art Large-scale Pretrained Response generation model (DialoGPT)"
examples = [["How are you?"]]
model = AutoModelForQuestionAnswering.from_pretrained("bert-large-uncased-whole-word-masking-finetuned-squad",return_dict=False)
tokenizer = AutoTokenizer.from_pretrained("bert-large-uncased-whole-word-masking-finetuned-squad")
nlp = pipeline("question-answering", model=model, tokenizer=tokenizer)
# tokenizer = AutoTokenizer.from_pretrained("microsoft/DialoGPT-large")
# model = AutoModelForCausalLM.from_pretrained("microsoft/DialoGPT-large")
def func(context, question):
result = nlp(question = question, context=context)
return result['answer']
app = gr.Interface(fn=func, inputs = ['textbox', 'text'], outputs = 'textbox', title = 'Farm QA Bot', theme = 'dark-grass', description = 'Input context and question, then get answers!')
app.launch(inline=False) |