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license: openrail++ |
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# Terminus XL Otaku (v1 preview) |
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## Model Details |
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### Model Description |
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Terminus XL Otaku is a latent diffusion model that uses zero-terminal SNR noise schedule and velocity prediction objective at training and inference time. |
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Terminus is a new state-of-the-art model family based on SDXL's architecture, and is compatible with (most) SDXL pipelines. |
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For Terminus Otaku (this model), the training data is exclusively anime/celshading/3D renders and other hand-drawn or synthetic art styles. |
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The objective of this model was to continue the use of v-prediction objective and min-SNR gamma loss to adapt Terminus Gamma v2's outputs to a more artistic style. |
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- **Fine-tuned from:** ptx0/terminus-xl-gamma-v2 |
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- **Developed by:** pseudoterminal X (@bghira) |
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- **Funded by:** pseudoterminal X (@bghira) |
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- **Model type:** Latent Diffusion |
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- **License:** openrail++ |
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- **Architecture:** SDXL |
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### Model Sources |
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- **Repository:** https://github.com/bghira/SimpleTuner |
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## Uses |
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### Direct Use |
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Terminus XL Otaku can be used for generating high-quality images given text prompts. |
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It should particularly excel at inpainting tasks for animated subject matter, where a zero-terminal SNR noise schedule allows it to more effectively retain contrast. |
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The model can be utilized in creative industries such as art, advertising, and entertainment to create visually appealing content. |
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### Downstream Use |
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Terminus XL Otaku can be fine-tuned for specific tasks such as image super-resolution, style transfer, and more. |
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However, it's recommended that the v1 preview not be used for fine-tuning until it is fully released, as any structural issues will hopefully be resolved by then. |
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### Out-of-Scope Use |
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The model is not designed for tasks outside of image generation. It should not be used to produce harmful content, or deceive others. Please use common sense. |
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## Bias, Risks, and Limitations |
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The model might exhibit biases present in the training data. The generated images should be carefully reviewed to ensure they meet ethical and societal standards. |
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### Recommendations |
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Users should be cautious of potential biases in the generated images and thoroughly review them before use. |
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## Training Details |
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### Training Data |
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This model's success largely depended on a somewhat small collection of very high quality data samples. |
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* Indiscriminate use of NijiJourney outputs. |
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* Midjourney 5.2 outputs that mention anime styles in their tags. |
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* Niji and MJ Showcase images that were re-captioned using CogVLM. |
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* Anchor data of real human subjects in a small (10%) ratio to the animated material, to retain coherence. |
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### Training Procedure |
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#### Preprocessing |
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This model is (so far) trained exclusively on cropped images using SDXL's crop coordinates to improve fine details. |
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No images were upsampled or downsampled during this training session. Instead, random crops (or unaltered 1024px square images) were used in lieu. |
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~50,000 images were used for this training run with continuous collection throughout the process, making it difficult to ascertain how many exact images were used. |
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#### Training Hyperparameters |
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- **Training regime:** bf16 mixed precision |
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- **Learning rate:** \(1 \times 10^{-7}\) to \(1 \times 10^{-6}\), cosine schedule |
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- **Epochs:** 11 |
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- **Batch size:** 12 * 8 = 96 |
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#### Speeds, Sizes, Times |
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[More Information Needed] |
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## Evaluation |
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### Testing Data, Factors & Metrics |
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[More Information Needed] |
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### Results |
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[More Information Needed] |
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#### Summary |
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[More Information Needed] |
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## Environmental Impact |
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- **Hardware Type:** [More Information Needed] |
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- **Hours used:** [More Information Needed] |
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- **Cloud Provider:** [More Information Needed] |
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- **Compute Region:** [More Information Needed] |
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- **Carbon Emitted:** [More Information Needed] |
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## Technical Specifications |
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### Model Architecture and Objective |
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The model uses an SDXL-compatible latent diffusion architecture with a unique min-SNR augmented velocity objective. |
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### Compute Infrastructure |
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[More Information Needed] |
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#### Hardware |
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[More Information Needed] |
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#### Software |
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[More Information Needed] |
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## Citation |
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**BibTeX:** |
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[More Information Needed] |
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**APA:** |
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[More Information Needed] |
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## Glossary |
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[More Information Needed] |
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## More Information |
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[More Information Needed] |
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## Model Card Authors |
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[More Information Needed] |
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## Model Card Contact |
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[More Information Needed] |
