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from transformers import AutoTokenizer, AutoModelForSequenceClassification | |
import torch | |
# Load the Hugging Face model and tokenizer | |
model_name = "ahmedheakl/bert-resume-classification" | |
tokenizer = AutoTokenizer.from_pretrained(model_name) | |
model = AutoModelForSequenceClassification.from_pretrained(model_name) | |
def classify_text(text): | |
inputs = tokenizer(text, return_tensors="pt", | |
truncation=True, padding=True) | |
outputs = model(**inputs) | |
probabilities = torch.nn.functional.softmax(outputs.logits, dim=-1) | |
predicted_class = torch.argmax(probabilities).item() | |
return predicted_class | |