Create model_loader.py
Browse files- model_loader.py +20 -0
model_loader.py
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# model_loader.py
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from transformers import AutoModelForSequenceClassification, AutoTokenizer
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def load_model_and_tokenizer():
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"""
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Load the fine-tuned XLM-RoBERTa model and tokenizer.
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Returns the model and tokenizer for use in classification.
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"""
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try:
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model_name = "your_username/xlm-roberta-toxic-classifier" # Replace with your model repo ID
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# If the model is local: model_name = "./model"
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model = AutoModelForSequenceClassification.from_pretrained(model_name)
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tokenizer = AutoTokenizer.from_pretrained(model_name)
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return model, tokenizer
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except Exception as e:
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raise Exception(f"Error loading model or tokenizer: {str(e)}")
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# Load the model and tokenizer once at startup
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model, tokenizer = load_model_and_tokenizer()
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