Why Bloom tokenizer use padding to max_length it will placed the padding tokens to the head ?
As the title say,
The following snippet produce:
```python
native_tokenizer = AutoTokenizer.from_pretrained("bigscience/bloom-560m", 
                                                      use_fast=False)
caption = "a bear in the woods."
tokenized_data = native_tokenizer(
          caption,
          return_tensors="pt",
          padding='max_length',
          truncation=True,
          max_length=56)
tokens = tokenized_data.input_ids[0]
tokens
```
produce:
```python
tensor([     3,      3,      3,      3,      3,      3,      3,      3,      3,
             3,      3,      3,      3,      3,      3,      3,      3,      3,
             3,      3,      3,      3,      3,      3,      3,      3,      3,
             3,      3,      3,      3,      3,      3,      3,      3,      3,
             3,      3,      3,      3,      3,      3,      3,      3,      3,
             3,      3,      3,      3,      3,     68,  50507,    361,    368,
        165526,     17])
```
It pad the pad_token_id "3" to the head, not tail.
This is different with other models.
Why this occurred ?
That's because BLOOM is a generative models, and when using `generate` padding should go on the left for better results. This is thus the default behavior of its tokenizer.<|||||>> That's because BLOOM is a generative models, and when using `generate` padding should go on the left for better results. This is thus the default behavior of its tokenizer.

Is there exist a build in simple api method to change this  activity ?<|||||>This issue has been automatically marked as stale because it has not had recent activity. If you think this still needs to be addressed please comment on this thread.

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