Hello!
For BertForSequenceClassification
you can do almost exactly what you did with BertModel
:
>>> model = BertForSequenceClassification.from_pretrained("bert-base-uncased")
>>> model.bert.embeddings.word_embeddings.weight
Parameter containing:
tensor([[-0.0102, -0.0615, -0.0265, ..., -0.0199, -0.0372, -0.0098],
[-0.0117, -0.0600, -0.0323, ..., -0.0168, -0.0401, -0.0107],
[-0.0198, -0.0627, -0.0326, ..., -0.0165, -0.0420, -0.0032],
...,
[-0.0218, -0.0556, -0.0135, ..., -0.0043, -0.0151, -0.0249],
[-0.0462, -0.0565, -0.0019, ..., 0.0157, -0.0139, -0.0095],
[ 0.0015, -0.0821, -0.0160, ..., -0.0081, -0.0475, 0.0753]],
requires_grad=True)