Update README.md
Browse files
README.md
CHANGED
|
@@ -21,6 +21,8 @@ pipeline_tag: text-to-image
|
|
| 21 |
|
| 22 |
To enhance performance and tailor the model to specific use cases, SDXL is fine-tuned using <strong>QLoRA (Quantized Low-Rank Adaptation)</strong>. This approach leverages efficient parameter fine-tuning and memory optimization techniques, enabling high-quality adaptations with reduced computational overhead. Fine-tuning with QLoRA ensures that the model is optimized for domain-specific text-to-image tasks, delivering even more precise and creative outputs.
|
| 23 |
|
|
|
|
|
|
|
| 24 |
<p style="font-family:Lucida Sans ;font-size:15px;">Dataset Description: CelebFaces Attributes Dataset (CelebA).</p>
|
| 25 |
|
| 26 |
<p style="font-family: Lucida Sans ;font-size:15px;">The CelebA dataset is a widely-used, large-scale dataset in the field of computer vision, particularly for tasks related to faces. It consists of over 200,000 celebrity face images annotated with a rich set of attributes. The dataset offers diverse visual content with variations in pose, facial expressions, and backgrounds, making it suitable for a range of face-related applications.</p>
|
|
|
|
| 21 |
|
| 22 |
To enhance performance and tailor the model to specific use cases, SDXL is fine-tuned using <strong>QLoRA (Quantized Low-Rank Adaptation)</strong>. This approach leverages efficient parameter fine-tuning and memory optimization techniques, enabling high-quality adaptations with reduced computational overhead. Fine-tuning with QLoRA ensures that the model is optimized for domain-specific text-to-image tasks, delivering even more precise and creative outputs.
|
| 23 |
|
| 24 |
+
Simplified Architecture: 
|
| 25 |
+
|
| 26 |
<p style="font-family:Lucida Sans ;font-size:15px;">Dataset Description: CelebFaces Attributes Dataset (CelebA).</p>
|
| 27 |
|
| 28 |
<p style="font-family: Lucida Sans ;font-size:15px;">The CelebA dataset is a widely-used, large-scale dataset in the field of computer vision, particularly for tasks related to faces. It consists of over 200,000 celebrity face images annotated with a rich set of attributes. The dataset offers diverse visual content with variations in pose, facial expressions, and backgrounds, making it suitable for a range of face-related applications.</p>
|