PseudoTerminal X
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Commit
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Parent(s):
d15be64
Trained for 0 epochs and 6000 steps.
Browse filesTrained with datasets ['text-embeds-pixart-filter', 'photo-concept-bucket', 'moviecollection', 'experimental', 'ethnic', 'sports', 'architecture', 'shutterstock', 'cinemamix-1mp', 'nsfw-1024', 'anatomy', 'bg20k-1024', 'yoga', 'photo-aesthetics', 'text-1mp', 'movieposters', 'normalnudes', 'pixel-art', 'signs', 'midjourney-v6-520k-raw', 'sfwbooru', 'nijijourney-v6-520k-raw', 'dalle3']
Learning rate 1e-06, batch size 24, and 1 gradient accumulation steps.
Used DDPM noise scheduler for training with epsilon prediction type and rescaled_betas_zero_snr=False
Using 'linspace' timestep spacing.
Base model: ptx0/pixart-900m-1024-ft-large
VAE: madebyollin/sdxl-vae-fp16-fix
- README.md +6 -6
- optimizer.bin +1 -1
- random_states_0.pkl +2 -2
- scheduler.bin +1 -1
- training_state-anatomy.json +0 -0
- training_state-dalle3.json +0 -0
- training_state-midjourney-v6-520k-raw.json +0 -0
- training_state-nijijourney-v6-520k-raw.json +0 -0
- training_state-photo-concept-bucket.json +2 -2
- training_state-sfwbooru.json +0 -0
- training_state-text-1mp.json +0 -0
- training_state.json +1 -1
- transformer/diffusion_pytorch_model.safetensors +1 -1
README.md
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@@ -77,7 +77,7 @@ 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: 1e-06
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- Effective batch size: 192
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- Micro-batch size: 24
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- Crop aspect: random
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### anatomy
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- Repeats: 5
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- Total number of images: ~
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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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### midjourney-v6-520k-raw
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- Repeats: 0
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- Total number of images: ~671104
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-
- Total number of aspect buckets:
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- Resolution: 1.0 megapixels
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- Cropped: False
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- Crop style: None
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### sfwbooru
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- Repeats: 0
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- Total number of images: ~423552
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-
- Total number of aspect buckets:
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- Resolution: 1.0 megapixels
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- Cropped: False
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- Crop style: None
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### nijijourney-v6-520k-raw
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- Repeats: 0
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- Total number of images: ~670976
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-
- Total number of aspect buckets:
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- Resolution: 1.0 megapixels
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- Cropped: False
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- Crop style: None
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## Training settings
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- Training epochs: 0
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+
- Training steps: 6000
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- Learning rate: 1e-06
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- Effective batch size: 192
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- Micro-batch size: 24
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- Crop aspect: random
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### anatomy
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- Repeats: 5
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- Total number of images: ~15168
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- Total number of aspect buckets: 3
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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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### midjourney-v6-520k-raw
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- Repeats: 0
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- Total number of images: ~671104
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- Total number of aspect buckets: 10
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- Resolution: 1.0 megapixels
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- Cropped: False
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- Crop style: None
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### sfwbooru
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- Repeats: 0
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- Total number of images: ~423552
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- Total number of aspect buckets: 25
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- Resolution: 1.0 megapixels
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- Cropped: False
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- Crop style: None
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### nijijourney-v6-520k-raw
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- Repeats: 0
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- Total number of images: ~670976
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+
- Total number of aspect buckets: 9
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- Resolution: 1.0 megapixels
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- Cropped: False
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- Crop style: None
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optimizer.bin
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random_states_0.pkl
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scheduler.bin
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training_state-anatomy.json
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training_state-dalle3.json
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training_state-midjourney-v6-520k-raw.json
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training_state-nijijourney-v6-520k-raw.json
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training_state-photo-concept-bucket.json
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training_state-sfwbooru.json
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training_state-text-1mp.json
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training_state.json
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{"global_step":
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{"global_step": 6000, "epoch_step": 1, "epoch": 1, "exhausted_backends": ["signs", "nijijourney", "pixel-art", "propagandaposters", "sports", "gay", "experimental", "yoga", "ethnic", "cinemamix-1mp", "architecture", "mj-60", "normalnudes", "bookcovers", "celebrities", "movieposters", "shutterstock", "nsfw-1024", "photo-aesthetics", "moviecollection", "bg20k-1024"], "repeats": {"bookcovers": 0, "signs": 0, "normalnudes": 0, "nijijourney": 0, "movieposters": 0, "celebrities": 0, "pixel-art": 0, "propagandaposters": 0, "sports": 0, "moviecollection": 0, "gay": 0, "experimental": 0, "yoga": 0, "ethnic": 0, "cinemamix-1mp": 0, "architecture": 0, "mj-60": 0, "text-1mp": 13, "shutterstock": 0, "nsfw-1024": 0, "photo-aesthetics": 0, "anatomy": 5, "bg20k-1024": 0}}
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transformer/diffusion_pytorch_model.safetensors
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