import torch
from transformers import AutoTokenizer, AutoModelForSequenceClassification

tokenizer = AutoTokenizer.from_pretrained("fdlvaaa/rubert-toxicity-classifier")
model = AutoModelForSequenceClassification.from_pretrained("fdlvaaa/rubert-toxicity-classifier")

text = "Здравствуйте, чем могу помочь?"
inputs = tokenizer(text, return_tensors='pt', truncation=True, max_length=512)

with torch.no_grad():
    outputs = model(**inputs)
    probs = torch.softmax(outputs.logits, dim=-1)

toxicity_prob = probs[0][1].item()
label = 'Токсично' if toxicity_prob >= 0.5 else 'Безопасно'
print(f"Результат: {label} | Вероятность: {toxicity_prob:.4f}")