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Let tokenizers return weights to be stored in the saved checkpoint.
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@@ -34,6 +34,9 @@ class SD3Tokenizer:
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def untokenize(self, token_weight_pair):
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return self.clip_g.untokenize(token_weight_pair)
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def state_dict(self):
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return {}
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class SD3ClipModel(torch.nn.Module):
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def __init__(self, clip_l=True, clip_g=True, t5=True, dtype_t5=None, device="cpu", dtype=None):
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super().__init__()
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