@joeddav Could you please suggest what’s the recommended way to do what Exbert does with our own weights (seeing which token in sentence the model pays attention to) ? HF Exbert works for default pretrained LMs, I want my trained weights to be used for inference task. I’m running experiments on server, building npm and other stuff seems like a lot of work, but I think things may have changed a bit after introduction on HF inference API. I’m using bert-base-uncased (pretty standard), want to load weights from HF model hub instead.