| Certainly! Below are two model card templates for your models: **Stable Diffusion Finetuned** and **PRNet 3D Face Reconstruction**. These model cards can be published on Hugging Face or similar platforms to provide useful information about each model, including usage, limitations, and training details. |
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| ### Model Card: **Stable Diffusion Finetuned** |
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| **Model Name**: `stable-diffusion-finetuned` |
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| #### Model Description: |
| This is a fine-tuned version of the Stable Diffusion model, a state-of-the-art generative model capable of producing high-quality images from textual descriptions. The model has been fine-tuned on a custom dataset for improved performance in a specific domain. |
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| - **Architecture**: Stable Diffusion |
| - **Base Model**: Stable Diffusion 1.x (before fine-tuning) |
| - **Training Data**: Custom dataset of images and corresponding textual descriptions. |
| - **Purpose**: This model is intended for generating images based on specific domain-related text descriptions (e.g., architecture, landscapes, characters). |
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| #### Model Details: |
| - **Training**: Fine-tuned using Google Colab with the Stable Diffusion base model. The training used the free quota on Colab and was optimized for generating images based on domain-specific prompts. |
| - **Optimizations**: The model was fine-tuned for a reduced number of epochs to prevent overfitting and to ensure generalizability across different prompts. |
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| #### Usage: |
| This model is intended for generating images from text inputs. The quality of generated images may vary based on the input prompt and the specificity of the fine-tuning dataset. |
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| ##### Example: |
| ```python |
| from transformers import StableDiffusionPipeline |
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| pipe = StableDiffusionPipeline.from_pretrained("your-hf-username/stable-diffusion-finetuned") |
| prompt = "A scenic view of mountains during sunset" |
| image = pipe(prompt).images[0] |
| image.show() |
| ``` |
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| #### Intended Use: |
| - **Domain-Specific Image Generation**: Designed to generate images for specific scenarios (e.g., concept art, landscape images, etc.). |
| - **Text-to-Image**: Works by taking text prompts and producing visually coherent images. |
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| #### Limitations and Risks: |
| - **Bias in Generation**: Since the model was fine-tuned on a specific dataset, it may produce biased outputs, and its applicability outside the fine-tuned domain may be limited. |
| - **Sensitive Content**: The model may inadvertently generate inappropriate or unintended imagery depending on the prompt. |
| - **Performance**: Since the model was trained on limited resources (free Colab), generation may not be as fast or optimized for large-scale use cases. |
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| #### How to Cite: |
| If you use this model, please cite the original Stable Diffusion authors and mention that this version is fine-tuned for specific tasks: |
| ``` |
| @misc{stable-diffusion-finetuned, |
| title={Stable Diffusion Finetuned Model}, |
| author={Mostafa Aly}, |
| year={2024}, |
| howpublished={\url{https://huggingface.co/your-hf-username/stable-diffusion-finetuned}}, |
| } |
| ``` |
