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distilbert-base-uncased) trained to classify customer support tickets into 27 specific intents across 11 major categories.cancel_order, recover_password, edit_account, etc.)best_model_state.bin: The trained PyTorch model weights.tokenizer/: Full configuration for the BERT tokenizer.label_encoder.joblib: The mapping for the 27 intent classes.huggingface_hub library to download the artifacts into the models/ directory of the main project.1from transformers import DistilBertForSequenceClassification, DistilBertTokenizer
2import torch
3
4# Path to the downloaded model
5model = DistilBertForSequenceClassification.from_pretrained("./models/tokenizer", num_labels=27)
6model.load_state_dict(torch.load("./models/best_model_state.bin"))