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generate_text
Browse files- .idea/vcs.xml +0 -1
- functions/generate_text.py +38 -0
.idea/vcs.xml
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@@ -2,6 +2,5 @@
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<project version="4">
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<component name="VcsDirectoryMappings">
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<mapping directory="$PROJECT_DIR$" vcs="Git" />
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-
<mapping directory="$PROJECT_DIR$/neuralwebsite" vcs="Git" />
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</component>
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</project>
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<project version="4">
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<component name="VcsDirectoryMappings">
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<mapping directory="$PROJECT_DIR$" vcs="Git" />
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</component>
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</project>
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functions/generate_text.py
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@@ -0,0 +1,38 @@
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from config import model_gt
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import torch
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from transformers import GPT2Tokenizer, GPT2LMHeadModel
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tokenizer = GPT2Tokenizer.from_pretrained(model_gt)
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model = GPT2LMHeadModel.from_pretrained(model_gt)
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# text = "Replace me by any text you'd like."
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# encoded_input = tokenizer(text, return_tensors='tf')
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# output = model(encoded_input)
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def generate_text(prompt:str, max_length:int=100)->str:
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"""
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Генерирует продолжение текста на основе заданного промпта.
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"""
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try:
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inputs = tokenizer(prompt,
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return_tensors="pt", # PyTorch тензоры
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truncation=True,
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padding=True,
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max_length=512)
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with torch.no_grad():
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outputs=model.generate(
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input_ids=inputs.input_ids,
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attention_mask=inputs.attention_mask,
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max_length=max_length,
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num_return_sequences=1,
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pad_token_id=tokenizer.eos_token_id,
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do_sample=True, # включаем вероятностную выборку
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temperature=0.7 # креативность (0 – детерминированно, 1 – случайно)
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)
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generated_text = tokenizer.decode(outputs[0], skip_special_tokens=True)
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return generated_text
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except Exception as e:
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return f'error of generaion: {str(e)}'
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