Update README.md
Browse files
README.md
CHANGED
|
@@ -13,6 +13,8 @@ inference: false
|
|
| 13 |
|
| 14 |
# SD-XL Inpainting 0.1 Model Card
|
| 15 |
|
|
|
|
|
|
|
| 16 |
SD-XL Inpainting 0.1 is a latent text-to-image diffusion model capable of generating photo-realistic images given any text input, with the extra capability of inpainting the pictures by using a mask.
|
| 17 |
|
| 18 |
The SD-XL Inpainting 0.1 was initialized with the `stable-diffusion-xl-base-1.0` weights. The model is trained for 40k steps at resolution 1024x1024 and 5% dropping of the text-conditioning to improve classifier-free classifier-free guidance sampling. For inpainting, the UNet has 5 additional input channels (4 for the encoded masked-image and 1 for the mask itself) whose weights were zero-initialized after restoring the non-inpainting checkpoint. During training, we generate synthetic masks and, in 25% mask everything.
|
|
|
|
| 13 |
|
| 14 |
# SD-XL Inpainting 0.1 Model Card
|
| 15 |
|
| 16 |
+

|
| 17 |
+
|
| 18 |
SD-XL Inpainting 0.1 is a latent text-to-image diffusion model capable of generating photo-realistic images given any text input, with the extra capability of inpainting the pictures by using a mask.
|
| 19 |
|
| 20 |
The SD-XL Inpainting 0.1 was initialized with the `stable-diffusion-xl-base-1.0` weights. The model is trained for 40k steps at resolution 1024x1024 and 5% dropping of the text-conditioning to improve classifier-free classifier-free guidance sampling. For inpainting, the UNet has 5 additional input channels (4 for the encoded masked-image and 1 for the mask itself) whose weights were zero-initialized after restoring the non-inpainting checkpoint. During training, we generate synthetic masks and, in 25% mask everything.
|