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I have a Megatron LM checkpoint trained using ALIBI. Since ALIBI doesn't add positional embeddings, I don't have it in my checkpoints as well.
During conversion of my checkpoint to HF transformers checkpoint, using src/transformers/models/megatron_gpt_bigcode/checkpoint_reshaping_and_interoperability.py , I get the below error.
AttributeError: 'dict' object has not attribute 'to'
This is because, I believe, the function get_element_from_dict_by_path is not consistent with it's return type.
It returns positional embeddings(tensors) when I have the positional embedding.
It returns empty dictionary when I don't have it. (in my case)
The issue arises later when we try to convert data type of the output from the above function in line 412.
Can we add support for checkpoints trained using ALIBI ?
The text was updated successfully, but these errors were encountered:
I have a Megatron LM checkpoint trained using ALIBI. Since ALIBI doesn't add positional embeddings, I don't have it in my checkpoints as well.
During conversion of my checkpoint to HF transformers checkpoint, using src/transformers/models/megatron_gpt_bigcode/checkpoint_reshaping_and_interoperability.py , I get the below error.
AttributeError: 'dict' object has not attribute 'to'
This is because, I believe, the function get_element_from_dict_by_path is not consistent with it's return type.
It returns positional embeddings(tensors) when I have the positional embedding.
It returns empty dictionary when I don't have it. (in my case)
The issue arises later when we try to convert data type of the output from the above function in line 412.
Can we add support for checkpoints trained using ALIBI ?
The text was updated successfully, but these errors were encountered: