Create app.py
Browse files
app.py
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import streamlit as st
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from transformers import AutoTokenizer, AutoModelForCausalLM
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import torch
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# Загрузка модели
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tokenizer = AutoTokenizer.from_pretrained("sberbank-ai/rugpt3small_based_on_gpt2")
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model = AutoModelForCausalLM.from_pretrained("sberbank-ai/rugpt3small_based_on_gpt2")
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device = torch.device("cpu")
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# Функция для генерации текста
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def generate_text(prompt):
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input_ids = tokenizer.encode(prompt, return_tensors="pt").to(device)
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output = model.generate(input_ids, max_length=50, do_sample=True)
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generated_text = tokenizer.decode(output[0], skip_special_tokens=True)
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return generated_text
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# Заголовок страницы
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st.title("RuGPT-3 Demo")
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# Ввод текста пользователем
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prompt = st.text_input("Введите текст:")
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if prompt:
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# Генерация ответа
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response = generate_text("USER: " + prompt + " AI:")
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# Отображение ответа
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st.write(response)
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