Added dataset tagging and management tools using llava
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@@ -133,6 +133,7 @@ class TrainConfig:
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# we will predict noise without a the LoRa network and use the prediction as a target for
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# unmasked reign. It is unmasked regularization basically
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self.inverted_mask_prior = kwargs.get('inverted_mask_prior', False)
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self.inverted_mask_prior_multiplier = kwargs.get('inverted_mask_prior_multiplier', 0.5)
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# legacy
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if match_adapter_assist and self.match_adapter_chance == 0.0:
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