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--- |
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license: creativeml-openrail-m |
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base_model: "ptx0/pixart-900m-1024-ft-large" |
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tags: |
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- stable-diffusion |
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- stable-diffusion-diffusers |
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- text-to-image |
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- diffusers |
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- simpletuner |
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- full |
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inference: true |
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widget: |
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- text: 'unconditional (blank prompt)' |
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parameters: |
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negative_prompt: 'blurry, cropped, ugly' |
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output: |
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url: ./assets/image_0_0.png |
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- text: 'unconditional (blank prompt)' |
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parameters: |
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negative_prompt: 'blurry, cropped, ugly' |
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output: |
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url: ./assets/image_1_1.png |
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- text: 'unconditional (blank prompt)' |
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parameters: |
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negative_prompt: 'blurry, cropped, ugly' |
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output: |
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url: ./assets/image_2_2.png |
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- text: 'ethnographic photography of teddy bear at a picnic holding a sign that reads SOON' |
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parameters: |
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negative_prompt: 'blurry, cropped, ugly' |
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output: |
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url: ./assets/image_3_0.png |
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- text: 'ethnographic photography of teddy bear at a picnic holding a sign that reads SOON' |
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parameters: |
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negative_prompt: 'blurry, cropped, ugly' |
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output: |
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url: ./assets/image_4_1.png |
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- text: 'ethnographic photography of teddy bear at a picnic holding a sign that reads SOON' |
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parameters: |
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negative_prompt: 'blurry, cropped, ugly' |
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output: |
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url: ./assets/image_5_2.png |
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--- |
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# pixart-900m-1024-ft |
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This is a full rank finetune derived from [ptx0/pixart-900m-1024-ft-large](https://huggingface.co/ptx0/pixart-900m-1024-ft-large). |
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The main validation prompt used during training was: |
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``` |
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ethnographic photography of teddy bear at a picnic holding a sign that reads SOON |
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``` |
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## Validation settings |
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- CFG: `7.5` |
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- CFG Rescale: `0.0` |
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- Steps: `30` |
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- Sampler: `euler` |
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- Seed: `42` |
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- Resolutions: `1024x1024,1344x768,916x1152` |
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Note: The validation settings are not necessarily the same as the [training settings](#training-settings). |
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You can find some example images in the following gallery: |
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<Gallery /> |
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The text encoder **was not** trained. |
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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: 13500 |
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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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- Gradient accumulation steps: 1 |
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- Number of GPUs: 8 |
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- Prediction type: epsilon |
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- Rescaled betas zero SNR: False |
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- Optimizer: AdamW, stochastic bf16 |
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- Precision: Pure BF16 |
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- Xformers: Not used |
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## Datasets |
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### photo-concept-bucket |
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- Repeats: 0 |
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- Total number of images: ~703040 |
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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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- Crop aspect: random |
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### moviecollection |
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- Repeats: 15 |
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- Total number of images: ~768 |
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- Total number of aspect buckets: 11 |
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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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- Crop aspect: random |
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### experimental |
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- Repeats: 0 |
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- Total number of images: ~1728 |
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- Total number of aspect buckets: 11 |
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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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- Crop aspect: random |
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### ethnic |
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- Repeats: 0 |
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- Total number of images: ~1152 |
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- Total number of aspect buckets: 7 |
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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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- Crop aspect: random |
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### sports |
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- Repeats: 0 |
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- Total number of images: ~576 |
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- Total number of aspect buckets: 1 |
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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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- Crop aspect: square |
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### architecture |
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- Repeats: 0 |
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- Total number of images: ~4224 |
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- Total number of aspect buckets: 1 |
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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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- Crop aspect: square |
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### shutterstock |
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- Repeats: 0 |
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- Total number of images: ~14016 |
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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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- Crop aspect: random |
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### cinemamix-1mp |
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- Repeats: 0 |
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- Total number of images: ~7296 |
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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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- Crop aspect: random |
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### nsfw-1024 |
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- Repeats: 0 |
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- Total number of images: ~10368 |
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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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- 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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- Crop aspect: random |
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### bg20k-1024 |
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- Repeats: 0 |
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- Total number of images: ~89088 |
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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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- Crop aspect: random |
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### yoga |
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- Repeats: 0 |
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- Total number of images: ~2880 |
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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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- Crop aspect: random |
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### photo-aesthetics |
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- Repeats: 0 |
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- Total number of images: ~28608 |
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- Total number of aspect buckets: 17 |
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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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- Crop aspect: random |
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### text-1mp |
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- Repeats: 125 |
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- Total number of images: ~12864 |
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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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- Crop aspect: random |
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### movieposters |
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- Repeats: 10 |
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- Total number of images: ~192 |
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- Total number of aspect buckets: 1 |
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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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- Crop aspect: square |
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### normalnudes |
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- Repeats: 10 |
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- Total number of images: ~384 |
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- Total number of aspect buckets: 8 |
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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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- Crop aspect: random |
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### pixel-art |
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- Repeats: 0 |
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- Total number of images: ~384 |
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- Total number of aspect buckets: 11 |
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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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- Crop aspect: random |
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### signs |
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- Repeats: 0 |
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- Total number of images: ~384 |
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- Total number of aspect buckets: 1 |
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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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- Crop aspect: square |
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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: 2 |
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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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- Crop aspect: None |
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### sfwbooru |
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- Repeats: 0 |
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- Total number of images: ~271488 |
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- Total number of aspect buckets: 73 |
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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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- Crop aspect: 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: 1 |
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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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- Crop aspect: None |
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### dalle3 |
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- Repeats: 0 |
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- Total number of images: ~1242072 |
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- Total number of aspect buckets: 1 |
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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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- Crop aspect: None |
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## Inference |
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```python |
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import torch |
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from diffusers import DiffusionPipeline |
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model_id = 'pixart-900m-1024-ft' |
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prompt = 'ethnographic photography of teddy bear at a picnic holding a sign that reads SOON' |
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negative_prompt = 'blurry, cropped, ugly' |
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pipeline = DiffusionPipeline.from_pretrained(model_id) |
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pipeline.to('cuda' if torch.cuda.is_available() else 'mps' if torch.backends.mps.is_available() else 'cpu') |
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prompt = "ethnographic photography of teddy bear at a picnic holding a sign that reads SOON" |
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negative_prompt = "blurry, cropped, ugly" |
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pipeline = DiffusionPipeline.from_pretrained(model_id) |
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pipeline.to('cuda' if torch.cuda.is_available() else 'mps' if torch.backends.mps.is_available() else 'cpu') |
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image = pipeline( |
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prompt=prompt, |
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negative_prompt='blurry, cropped, ugly', |
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num_inference_steps=30, |
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generator=torch.Generator(device='cuda' if torch.cuda.is_available() else 'mps' if torch.backends.mps.is_available() else 'cpu').manual_seed(1641421826), |
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width=1152, |
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height=768, |
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guidance_scale=7.5, |
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guidance_rescale=0.0, |
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).images[0] |
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image.save("output.png", format="PNG") |
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``` |
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