To use this model ```python import torch from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("xlm-roberta-base") model = AutoModelForSequenceClassification.from_pretrained("LsTam/MQ-classification") softmax = torch.nn.Softmax(dim=1) prediction = lambda p : [(a[0] < a[1]) * 1 for a in p] # 0 is for wrong question and 1 for good ones text = ['Your question' + ' ' + 'your context'] a = tokenizer(text, return_tensors="pt") result = model(**a) pred = prediction(softmax(result.logits).tolist()) ```