Update README.md
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README.md
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@@ -26,6 +26,36 @@ I KNOW I KNOW, I'll get it worked out. For now this is epoch 9.
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# Most original checkpoints are default sd15 after testing
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For those who downloaded the models that either exhibit blobs or don't use flow matching noise - my sincerest apologies. They are defective. Blobs are expected, standard noise is not.
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As of epoch 11 the blobs are reforming back into shapes, and the shapes are cohesing in fairly utilizable ways for the end product, they are still however - blobs for the time being.
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This is a v-prediction flow-matching model that can be directly inferenced with euler-discreet flow-matching through diffusers, and I would advise doing this for testing purposes.
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# E11+ new expectations
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It's training directly with timestep-awareness using shift and timestep association.
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The least accurate timestep buckets have their opinions removed from the classifier weight, as the classifier cannot help if it cannot classify what the teacher itself is trying to say. Which lines up roughly with the 90/10 rule that David seems to cap at - which is about 90% accuracy and 10% incorrect. So about 10% of timestep buckets are inactive.
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Individual block losses have been correctly reintroduced and will train the timestep and patterns HOPEFULLY correctly.
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```
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# Timestep Weighting (David-guided adaptive sampling)
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use_timestep_weighting: bool = True
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use_david_weights: bool = True
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timestep_shift: float = 3.0 # SD3-style shift (higher = bias toward clean)
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base_jitter: int = 5 # Base ±jitter around bin center
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adaptive_chaos: bool = True # Scale jitter by pattern difficulty
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profile_samples: int = 2500 # Samples to profile David's difficulty
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reliability_threshold: float = 0.15 # Minimum accuracy to trust David's guidance
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```
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# Most original checkpoints are default sd15 after testing
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For those who downloaded the models that either exhibit blobs or don't use flow matching noise - my sincerest apologies. They are defective. Blobs are expected, standard noise is not.
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