Model card auto-generated by SimpleTuner
Browse files
README.md
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@@ -143,13 +143,13 @@ You may reuse the base model text encoder for inference.
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- Training steps: 100
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- Learning rate: 1e-05
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- Max grad norm: 0.01
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- Effective batch size:
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- Micro-batch size:
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- Gradient accumulation steps: 1
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- Number of GPUs: 3
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- Prediction type: flow-matching
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- Rescaled betas zero SNR: False
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- Optimizer: optimi-
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- Precision: Pure BF16
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- Quantised: Yes: int8-quanto
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- Xformers: Not used
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@@ -165,14 +165,11 @@ You may reuse the base model text encoder for inference.
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"factor": 12,
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"apply_preset": {
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"target_module": [
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"
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],
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"module_algo_map": {
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"
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"factor": 6
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},
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"JointTransformerBlock": {
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"factor": 12
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}
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}
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}
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- Training steps: 100
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- Learning rate: 1e-05
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- Max grad norm: 0.01
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- Effective batch size: 3
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- Micro-batch size: 1
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- Gradient accumulation steps: 1
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- Number of GPUs: 3
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- Prediction type: flow-matching
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- Rescaled betas zero SNR: False
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- Optimizer: optimi-stableadamw
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- Precision: Pure BF16
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- Quantised: Yes: int8-quanto
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- Xformers: Not used
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"factor": 12,
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"apply_preset": {
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"target_module": [
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"Attention"
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],
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"module_algo_map": {
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"Attention": {
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"factor": 6
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}
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}
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}
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