How to access attentions matrix for MarianMT?

### Question

Hey, I've been trying to access the attentions output by the MarianMT like so (please excuse the unorthodox config argument, tidying up is next on my todo list):

```
const model_name = "Xenova/opus-mt-en-fr";
const tokenizer = await MarianTokenizer.from_pretrained(model_name, {
config: {
output_hidden_states: true,
output_attentions: true
}
})
const tokens = (await tokenizer(text)).input_ids;
const model = await MarianMTModel.from_pretrained(model_name, {
config: {
model_type: 'marian',
is_encoder_decoder: true,
_name_or_path: 'Helsinki-NLP/opus-mt-en-fr',
_num_labels: 3,
activation_dropout: 0,
activation_function: 'swish',
add_bias_logits: false,
add_final_layer_norm: false,
architectures: ['MarianMTModel'],
attention_dropout: 0,
bad_words_ids: [[Array]],
bos_token_id: 0,
classif_dropout: 0,
classifier_dropout: 0,
d_model: 512,
decoder_attention_heads: 8,
decoder_ffn_dim: 2048,
decoder_layerdrop: 0,
decoder_layers: 6,
decoder_start_token_id: 59513,
decoder_vocab_size: 59514,
dropout: 0.1,
encoder_attention_heads: 8,
encoder_ffn_dim: 2048,
encoder_layerdrop: 0,
encoder_layers: 6,
eos_token_id: 0,
forced_eos_token_id: 0,
gradient_checkpointing: false,
id2label: { '0': 'LABEL_0', '1': 'LABEL_1', '2': 'LABEL_2' },
init_std: 0.02,
label2id: { LABEL_0: 0, LABEL_1: 1, LABEL_2: 2 },
max_length: 512,
max_position_embeddings: 512,
normalize_before: false,
normalize_embedding: false,
num_beams: 4,
num_hidden_layers: 6,
pad_token_id: 59513,
scale_embedding: true,
share_encoder_decoder_embeddings: true,
static_position_embeddings: true,
transformers_version: '4.34.0.dev0',
use_cache: true,
vocab_size: 59514,
output_hidden_states: true,
output_cross_attentions: true,
output_attentions: true
}
})
const translated = await model.generate(tokens)
const result = tokenizer.decode(translated[0], { skip_special_tokens: true })
console.log((await model.getAttentions(translated)))

```

I'm then getting the following error when I run the code:

`
Error: `output_attentions` is true, but the model did not produce cross-attentions. This is most likely because the model was not exported with `output_attentions=True`.
`

I've looked around but haven't been able to find out what is meant by the reference to exporting the model. How would I go about fixing this?