LsTam/MQ-classification

To use this model

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' + ' </s> ' + 'your context']

a = tokenizer(text, return_tensors="pt")
result = model(**a)
pred = prediction(softmax(result.logits).tolist())