def load_pretrained(self, wgts_fname:str, itos_fname:str, strict:bool=True):
        "Load a pretrained model and adapts it to the data vocabulary."
        old_itos = pickle.load(open(itos_fname, 'rb'))
        old_stoi = {v:k for k,v in enumerate(old_itos)}
        wgts = torch.load(wgts_fname, map_location=lambda storage, loc: storage)
        if 'model' in wgts: wgts = wgts['model']
        wgts = convert_weights(wgts, old_stoi, self.data.train_ds.vocab.itos)
        self.model.load_state_dict(wgts, strict=strict)
Load a pretrained model and adapts it to the data vocabulary.