How can I load a pretrained model on Kaggle using fastai?

Alright, it worked but now I am getting error, apparently the size of the weights have changed.

RuntimeError: Error(s) in loading state_dict for SequentialRNN:
size mismatch for 0.encoder.weight: copying a param with shape torch.Size([60002, 400]) from checkpoint, the shape in current model is torch.Size([7224, 400]).
size mismatch for 0.encoder_dp.emb.weight: copying a param with shape torch.Size([60002, 400]) from checkpoint, the shape in current model is torch.Size([7224, 400]).
size mismatch for 0.rnns.0.weight_hh_l0_raw: copying a param with shape torch.Size([4600, 1150]) from checkpoint, the shape in current model is torch.Size([4608, 1152]).
size mismatch for 0.rnns.0.module.weight_ih_l0: copying a param with shape torch.Size([4600, 400]) from checkpoint, the shape in current model is torch.Size([4608, 400]).
size mismatch for 0.rnns.0.module.weight_hh_l0: copying a param with shape torch.Size([4600, 1150]) from checkpoint, the shape in current model is torch.Size([4608, 1152]).
size mismatch for 0.rnns.0.module.bias_ih_l0: copying a param with shape torch.Size([4600]) from checkpoint, the shape in current model is torch.Size([4608]).
size mismatch for 0.rnns.0.module.bias_hh_l0: copying a param with shape torch.Size([4600]) from checkpoint, the shape in current model is torch.Size([4608]).
size mismatch for 0.rnns.1.weight_hh_l0_raw: copying a param with shape torch.Size([4600, 1150]) from checkpoint, the shape in current model is torch.Size([4608, 1152]).
size mismatch for 0.rnns.1.module.weight_ih_l0: copying a param with shape torch.Size([4600, 1150]) from checkpoint, the shape in current model is torch.Size([4608, 1152]).
size mismatch for 0.rnns.1.module.weight_hh_l0: copying a param with shape torch.Size([4600, 1150]) from checkpoint, the shape in current model is torch.Size([4608, 1152]).
size mismatch for 0.rnns.1.module.bias_ih_l0: copying a param with shape torch.Size([4600]) from checkpoint, the shape in current model is torch.Size([4608]).
size mismatch for 0.rnns.1.module.bias_hh_l0: copying a param with shape torch.Size([4600]) from checkpoint, the shape in current model is torch.Size([4608]).
size mismatch for 0.rnns.2.module.weight_ih_l0: copying a param with shape torch.Size([1600, 1150]) from checkpoint, the shape in current model is torch.Size([1600, 1152]).
size mismatch for 1.decoder.weight: copying a param with shape torch.Size([60002, 400]) from checkpoint, the shape in current model is torch.Size([7224, 400]).
size mismatch for 1.decoder.bias: copying a param with shape torch.Size([60002]) from checkpoint, the shape in current model is torch.Size([7224]).

found this Language_model_learner not working as before?
which removes the errors with loading of weights with shape 1552 now I am getting

RuntimeError: Error(s) in loading state_dict for SequentialRNN: size mismatch for 0.encoder.weight: copying a param with shape torch.Size([60002, 400]) from checkpoint, the shape in current model is torch.Size([7248, 400]). size mismatch for 0.encoder_dp.emb.weight: copying a param with shape torch.Size([60002, 400]) from checkpoint, the shape in current model is torch.Size([7248, 400]). size mismatch for 1.decoder.weight: copying a param with shape torch.Size([60002, 400]) from checkpoint, the shape in current model is torch.Size([7248, 400]). size mismatch for 1.decoder.bias: copying a param with shape torch.Size([60002]) from checkpoint, the shape in current model is torch.Size([7248]).