PseudoTerminal X
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Commit
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Parent(s):
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Trained for 0 epochs and 4900 steps.
Browse filesTrained with datasets ['text-embeds-sdxl', 'photocb-clip-embeds', 'celebrities', 'movieposters', 'normalnudes', 'propagandaposters', 'guys', 'pixel-art', 'signs', 'moviecollection', 'bookcovers', 'nijijourney', 'experimental', 'ethnic', 'sports', 'gay', 'architecture', 'shutterstock', 'cinemamix-1mp', 'nsfw-1024', 'anatomy', 'bg20k-1024', 'yoga', 'photo-aesthetics', 'text-1mp', 'photo-concept-bucket']
Learning rate 4e-07, batch size 8, and 4 gradient accumulation steps.
Used DDPM noise scheduler for training with v_prediction prediction type and rescaled_betas_zero_snr=True
Using 'trailing' timestep spacing.
Base model: ptx0/terminus-xl-velocity-v1
VAE: madebyollin/sdxl-vae-fp16-fix
- README.md +2 -2
- optimizer.bin +1 -1
- random_states_0.pkl +1 -1
- scheduler.bin +1 -1
- training_state-anatomy.json +2 -2
- training_state-architecture.json +2 -2
- training_state-bg20k-1024.json +2 -2
- training_state-cinemamix-1mp.json +2 -2
- training_state-experimental.json +2 -2
- training_state-nsfw-1024.json +2 -2
- training_state-photo-aesthetics.json +2 -2
- training_state-photo-concept-bucket.json +2 -2
- training_state-shutterstock.json +2 -2
- training_state-text-1mp.json +2 -2
- training_state-yoga.json +2 -2
- training_state.json +1 -1
- unet/config.json +1 -1
- unet/diffusion_pytorch_model.safetensors +1 -1
README.md
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@@ -44,7 +44,7 @@ You may reuse the base model text encoder for inference.
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## Training settings
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- Training epochs: 0
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- Training steps:
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- Learning rate: 4e-07
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- Effective batch size: 32
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- Micro-batch size: 8
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### architecture
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- Repeats: 0
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- Total number of images: 4324
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- Total number of aspect buckets:
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- Resolution: 1.0 megapixels
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- Cropped: True
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- Crop style: random
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## Training settings
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- Training epochs: 0
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- Training steps: 4900
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- Learning rate: 4e-07
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- Effective batch size: 32
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- Micro-batch size: 8
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### architecture
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- Repeats: 0
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- Total number of images: 4324
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- Total number of aspect buckets: 2
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- Resolution: 1.0 megapixels
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- Cropped: True
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- Crop style: random
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optimizer.bin
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