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README.md
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- text-to-image
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- stable-diffusion
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### Fine-Tune-Stable-Diffusion-model-for-Generating-My-pics Dreambooth model trained by zainikhan34 with [TheLastBen's fast-DreamBooth](https://colab.research.google.com/github/TheLastBen/fast-stable-diffusion/blob/main/fast-DreamBooth.ipynb) notebook
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Model Description
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This model is a fine-tuned version of the Stable Diffusion model using Dreambooth techniques. It is trained to generate high-quality images based on specific prompts, with a focus on generating images of the user.
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Training Data
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Dataset: The training dataset consists of 6 images of the user, Zain.
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Captions: All images were captioned with the user's name, "Zain".
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Preprocessing: Standard preprocessing steps were applied to the images.
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Training Procedure
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Training Method: Dreambooth
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UNet Training Steps: 1500
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UNet Learning Rate: 2e-6
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Resolution: 512
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Results
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Generated Images
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Here are some example images generated by the model:
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Intended Use
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This model is designed to generate personalized images based on the user's input. Potential applications include generating avatars, artistic portraits, and other creative outputs featuring the user.
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Limitations and Ethical Considerations
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Limitations: The model is not generating the user's face accurately, as the training images were taken from a distance and did not focus on the face.
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Ethical Considerations: Users should be aware of the ethical implications of using AI-generated images, particularly in terms of privacy and the potential for misuse.
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Thanks to TheLastBen's fast-DreamBooth notebook for providing the training framework.
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For further questions or collaborations, please contact zainikhan3434@gmail.com.
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- text-to-image
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- stable-diffusion
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# Fine-Tuned Stable Diffusion Model with Dreambooth
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## Model Description
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This model is a fine-tuned version of the Stable Diffusion model using Dreambooth techniques. It is trained to generate high-quality images based on specific prompts, with a focus on generating images of the user.
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## Training Data
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- **Dataset:** The training dataset consists of 6 images of the user, Zain.
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- **Captions:** All images were captioned with the user's name, "Zain".
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- **Preprocessing:** Standard preprocessing steps were applied to the images.
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## Training Procedure
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- **Training Method:** Dreambooth
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- **UNet Training Steps:** 1500
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- **UNet Learning Rate:** 2e-6
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- **Resolution:** 512
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## Results
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### Generated Images
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Here are some example images generated by the model:
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## Intended Use
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This model is designed to generate personalized images based on the user's input. Potential applications include generating avatars, artistic portraits, and other creative outputs featuring the user.
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## Limitations and Ethical Considerations
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- **Limitations:** The model is not generating the user's face accurately, as the training images were taken from a distance and did not focus on the face.
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- **Ethical Considerations:** Users should be aware of the ethical implications of using AI-generated images, particularly in terms of privacy and the potential for misuse.
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## How to Use
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Instructions on how to use the model can be found in the [Hugging Face documentation](https://huggingface.co/docs).
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## Acknowledgements
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- Thanks to [TheLastBen's fast-DreamBooth notebook](https://github.com/TheLastBen/fast-DreamBooth) for providing the training framework.
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## Contact
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For further questions or collaborations, please contact zainikhan3434@gmail.com.
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