Why the bias of config in train scripts doesn't aligning at infererence?

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When training, I found the bias doesn't align with the config.
This file is in the EAGLE3/eagle/train/main.py.

I think if do that, the result will produce the bias in "fc" layer due to following the default.

Maybe you should edit it because I find the model_state_dict of your official model doesn't have the fc.bias.

[870572761]

I raise this question because I find Model follow this json.