Tokenize the text and return the input_ids as PyTorch tensors. You'll also need to specify the position of the <mask> token:

from transformers import AutoTokenizer
tokenizer = AutoTokenizer.from_pretrained("username/my_awesome_eli5_mlm_model")
inputs = tokenizer(text, return_tensors="pt")
mask_token_index = torch.where(inputs["input_ids"] == tokenizer.mask_token_id)[1]

Pass your inputs to the model and return the logits of the masked token: