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  1. GPT.py +60 -0
  2. GPT_sonnik_only.pt +3 -0
GPT.py ADDED
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+ import streamlit as st
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+ import torch
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+ import numpy as np
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+ import transformers
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+ import random
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+
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+ def load_model():
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+ model_finetuned = transformers.AutoModelWithLMHead.from_pretrained(
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+ 'tinkoff-ai/ruDialoGPT-small',
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+ output_attentions = False,
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+ output_hidden_states = False
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+ )
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+ model_finetuned.load_state_dict(torch.load('GPT_sonnik_only.pt', map_location=torch.device('cpu')))
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+ tokenizer = transformers.AutoTokenizer.from_pretrained('tinkoff-ai/ruDialoGPT-small')
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+ return model_finetuned, tokenizer
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+
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+ def preprocess_text(text_input, tokenizer):
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+ prompt = tokenizer.encode(text_input, return_tensors='pt').to(device)
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+ return prompt
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+
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+ def predict_sentiment(model, prompt, temp, num_generate):
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+ result = model.generate(
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+ input_ids=prompt,
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+ max_length=150,
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+ num_beams=5,
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+ do_sample=True,
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+ temperature=float(temp),
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+ top_k=50,
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+ top_p=0.6,
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+ no_repeat_ngram_size=3,
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+ num_return_sequences=num_generate,
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+ ).cpu().numpy()
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+ return result
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+
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+ st.title('Text generation with dreambook')
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+
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+ model, tokenizer = load_model()
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+
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+ text_input = st.text_input("Enter some text about movie")
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+ max_len = st.slider('Length of sequence', 0, 500, 250)
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+ temp = st.slider('Temperature', 0, 30, 0)
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+ if st.button('Generate a random number of sequences'):
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+ num_generate = random.randint(1,5)
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+ st.write(f'Number of sequences: {num_generate}')
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+ else:
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+ num_generate = st.text_input("Enter number of sequences")
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+
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+ if text_input:
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+ prompt = preprocess_text(text_input, tokenizer)
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+ result = predict_sentiment(model, prompt, max_len, temp, num_generate)
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+ for i in result:
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+ st.write(textwrap.fill(tokenizer.decode(i), max_len))
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+ if st.button('Next'):
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+ try:
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+ continue
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+ except:
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+ st.write('All sequences are return. Generate new')
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+ else:
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+ None
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+
GPT_sonnik_only.pt ADDED
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+ version https://git-lfs.github.com/spec/v1
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+ oid sha256:c8263847502168c5dec7bc6aa2c46b183717eae05e03d38f7718a896a0e842e2
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+ size 551312985