Adding the support of dense models distilled from moe models with the same architecture#728
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Signed-off-by: Vahid Janfaza <vjanfaza@qti.qualcomm.com>
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In this PR, we are adding the support of meta-llama/Llama-Guard-4-12B which is a dense model distilled form llama4 scout moe model. The changes in pytorch_transforms.py file can be applied to any dense model distilled from a moe model with supported architecture in QEfficient.