use max sequence length for tokenization

[horheynm]

Fix bug for https://neuralmagic.slack.com/archives/C0592FX3215/p1687210067995879

Example:

from deepsparse import Pipeline


path = "path"

pipeline = Pipeline.create(
    task = "text-classification",
    model_path = path,
    batch_size=8,
    num_cores=None,
    sequence_length = [2, 128],
)

text = "We are flying from Texas to California"
pipeline(text)

Before:

(.venv) ubuntu@quad-mle-2:~/george/nm/deepsparse$ python3 scratch/_p.py 
...
2023-08-04 01:19:39 __main__     INFO     Overwriting in-place the input shapes of the transformer model at /home/ubuntu/.cache/sparsezoo/bert-large-squad_wikipedia_bookcorpus-pruned80.4block_quantized/bert-large-squad_wikipedia_bookcorpus-pruned80.4block_quantized/model.onnx
Token indices sequence length is longer than the specified maximum sequence length for this model (9 > 2). Running this sequence through the model will result in indexing errors

After"

(.venv) ubuntu@quad-mle-2:~/george/nm/deepsparse$ python3 scratch/_p.py 
...
2023-08-04 01:25:44 __main__     INFO     Overwriting in-place the input shapes of the transformer model at /home/ubuntu/.cache/sparsezoo/bert-large-squad_wikipedia_bookcorpus-pruned80.4block_quantized/bert-large-squad_wikipedia_bookcorpus-pruned80.4block_quantized/model.onnx

stale

[mgoin]

nice!