Thanks so much for the quick reply. I’m simply running this:
from transformers import BigBirdTokenizer, BigBirdModel

tokenizer = BigBirdTokenizer.from_pretrained('google/bigbird-roberta-base')
model = BigBirdModel.from_pretrained('google/bigbird-roberta-base')

inputs = tokenizer("Hello, my dog is cute", return_tensors="pt")
outputs = model(**inputs)
outputs

Perhaps it’s my dev configuration that’s the issue? I’m running my own conda environment with transformers v4.5.1, if that helps?
Edit: There’s also some logging provided that may be useful context:
Attention type 'block_sparse' is not possible if sequence_length: 8 <= num global tokens: 2 * config.block_size + min. num sliding tokens: 3 * config.block_size + config.num_random_blocks * config.block_size + additional buffer: config.num_random_blocks * config.block_size = 704 with config.block_size = 64, config.num_random_blocks = 3.Changing attention type to 'original_full'...