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| import torch | |
| from transformers import AutoTokenizer, AutoModelForSequenceClassification | |
| # Disk path where saved model & tokenizer is located | |
| save_dir = (r"./ml_engine/saved-model") #relative path acc. to "ebookify-backend/" directory (i.e the root directory of the backend) | |
| # Load the saved model and tokeniser from the disk | |
| loaded_tokeniser = AutoTokenizer.from_pretrained(save_dir) | |
| loaded_model = AutoModelForSequenceClassification.from_pretrained(save_dir) | |
| def is_it_title(string): | |
| # Input | |
| input = loaded_tokeniser(string, return_tensors='pt') | |
| with torch.no_grad(): | |
| output = loaded_model(**input).logits.item() | |
| # print(output.logits.item()) | |
| if(output >= 0.6): | |
| return True | |
| else: | |
| return False | |
| if __name__ == "__main__": | |
| print(is_it_title("Secret to Success lies in hardwork and nothing else!")) | |