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import os |
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from dotenv import load_dotenv |
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from transformers import TFBertForSequenceClassification, BertTokenizerFast |
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import tensorflow as tf |
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MODEL_NAME = "Erfan11/Neuracraft" |
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API_KEY = "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" |
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def load_model(model_name): |
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model = TFBertForSequenceClassification.from_pretrained(model_name, use_auth_token=API_KEY) |
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return model |
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def load_tokenizer(model_name): |
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tokenizer = BertTokenizerFast.from_pretrained(model_name, use_auth_token=API_KEY) |
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return tokenizer |
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def predict(text, model, tokenizer): |
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inputs = tokenizer(text, return_tensors="tf") |
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outputs = model(**inputs) |
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return outputs |
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def main(): |
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model_name = MODEL_NAME |
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model = load_model(model_name) |
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tokenizer = load_tokenizer(model_name) |
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text = "Sample input text" |
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result = predict(text, model, tokenizer) |
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print(result) |
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if __name__ == "__main__": |
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main() |