Allow EOS token for finetuning

[jimwu6]

This is needed to allow the finetuning dataset to be constructed correctly.

[dakinggg]

Where do you see this needed? I'm pretty sure finetuning just uses the eos from the tokenizer.

[milocress]

Where do you see this needed? I'm pretty sure finetuning just uses the eos from the tokenizer.

It looks like it's one of the things **ed into the superclass, I think there are some cases where omitting this causes an error. eg.

[rank2]: ValueError: sequence_id is a required argument when MPT is configured with attn_uses_sequence_id=True and the model is in train mode.

[dakinggg]

@milocress that should only be for pretraining style. finetuning style handles packing and sequence id on its own. e.g.

llm-foundry/llmfoundry/data/packing.py

Line 155 in fb9a225

trim_example['sequence_id'] = torch.zeros_like(trim_example['input_ids'])