Add Training Methods
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README.md
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@@ -129,6 +129,14 @@ The Segmind Stable Diffusion Model is suitable for research and practical applic
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- **Bias and Limitation Analysis:** Researchers and developers can use the model to probe its limitations and biases, contributing to a better understanding of generative models' behavior.
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### Out-of-Scope Use
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The SSD-1B Model is not suitable for creating factual or accurate representations of people, events, or real-world information. It is not intended for tasks requiring high precision and accuracy.
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- **Bias and Limitation Analysis:** Researchers and developers can use the model to probe its limitations and biases, contributing to a better understanding of generative models' behavior.
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### Downstream Use
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The Segmind Stable Diffusion Model can also be used directly with the 🧨 Diffusers library training scripts for further training, including:
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- **[Fine-Tune](https://github.com/huggingface/diffusers/blob/main/examples/text_to_image/train_text_to_image_sdxl.py)**
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- **[LoRA](https://github.com/huggingface/diffusers/blob/main/examples/text_to_image/train_text_to_image_lora_sdxl.py)**
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- **[Dreambooth LoRA](https://github.com/huggingface/diffusers/blob/main/examples/dreambooth/train_dreambooth_lora_sdxl.py)**
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### Out-of-Scope Use
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The SSD-1B Model is not suitable for creating factual or accurate representations of people, events, or real-world information. It is not intended for tasks requiring high precision and accuracy.
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