CODEWITHSUNDEEP
nlppytorchpre-trained-model
newbie
newbie

Reputation: 11

XLNetForSequenceClassification Pretrained model unable to load

I tried loading the XLNet pretrained but this occurred. I've tried this before and it worked, however, now it doesn't. Any suggestion on how to fix this problem?

model = XLNetForSequenceClassification.from_pretrained("xlnet-large-cased", num_labels = 2)
model.to(device)

---------------------------------------------------------------------------
RuntimeError                              Traceback (most recent call last)
<ipython-input-55-d6f698a3714b> in <module>()
----> 1 model = XLNetForSequenceClassification.from_pretrained("xlnet-large-cased", num_labels = 2)
      2 model.to(device)

3 frames
/usr/local/lib/python3.6/dist-packages/torch/nn/modules/sparse.py in __init__(self, num_embeddings, embedding_dim, padding_idx, max_norm, norm_type, scale_grad_by_freq, sparse, _weight)
     95         self.scale_grad_by_freq = scale_grad_by_freq
     96         if _weight is None:
---> 97             self.weight = Parameter(torch.Tensor(num_embeddings, embedding_dim))
     98             self.reset_parameters()
     99         else:

RuntimeError: Trying to create tensor with negative dimension -1: [-1, 1024]

Upvotes: 1

Views: 932

Answers (2)

Ajith Babu
Ajith Babu

Reputation: 11

You should import XLNetForSequenceClassification from transformers and not from pytorch-transformers. First, make sure transformers is installed:

> pip install transformers

Then, in your code:

from transformers import XLNetForSequenceClassification
model = XLNetForSequenceClassification.from_pretrained("xlnet-large-cased", num_labels = 2)

This should work.

Upvotes: 1

Arl N
Arl N

Reputation: 1

If you've not changed internally anything, most likely a version mismatch. Have you upgraded any relevant modules? Go back to previous version if you have that should solve it.

Pytorch Quantization RuntimeError: Trying to create tensor with negative dimension

Upvotes: 0

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