End of training
Browse files
README.md
ADDED
@@ -0,0 +1,62 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
1 |
+
---
|
2 |
+
license: openrail++
|
3 |
+
library_name: diffusers
|
4 |
+
tags:
|
5 |
+
- text-to-image
|
6 |
+
- text-to-image
|
7 |
+
- diffusers-training
|
8 |
+
- diffusers
|
9 |
+
- lora
|
10 |
+
- template:sd-lora
|
11 |
+
- stable-diffusion-xl
|
12 |
+
- stable-diffusion-xl-diffusers
|
13 |
+
base_model: stabilityai/stable-diffusion-xl-base-1.0
|
14 |
+
instance_prompt: In the style of TOK
|
15 |
+
widget: []
|
16 |
+
---
|
17 |
+
|
18 |
+
<!-- This model card has been generated automatically according to the information the training script had access to. You
|
19 |
+
should probably proofread and complete it, then remove this comment. -->
|
20 |
+
|
21 |
+
|
22 |
+
# SDXL LoRA DreamBooth - ayelets/yana_style
|
23 |
+
|
24 |
+
<Gallery />
|
25 |
+
|
26 |
+
## Model description
|
27 |
+
|
28 |
+
These are ayelets/yana_style LoRA adaption weights for stabilityai/stable-diffusion-xl-base-1.0.
|
29 |
+
|
30 |
+
The weights were trained using [DreamBooth](https://dreambooth.github.io/).
|
31 |
+
|
32 |
+
LoRA for the text encoder was enabled: False.
|
33 |
+
|
34 |
+
Special VAE used for training: madebyollin/sdxl-vae-fp16-fix.
|
35 |
+
|
36 |
+
## Trigger words
|
37 |
+
|
38 |
+
You should use In the style of TOK to trigger the image generation.
|
39 |
+
|
40 |
+
## Download model
|
41 |
+
|
42 |
+
Weights for this model are available in Safetensors format.
|
43 |
+
|
44 |
+
[Download](ayelets/yana_style/tree/main) them in the Files & versions tab.
|
45 |
+
|
46 |
+
|
47 |
+
|
48 |
+
## Intended uses & limitations
|
49 |
+
|
50 |
+
#### How to use
|
51 |
+
|
52 |
+
```python
|
53 |
+
# TODO: add an example code snippet for running this diffusion pipeline
|
54 |
+
```
|
55 |
+
|
56 |
+
#### Limitations and bias
|
57 |
+
|
58 |
+
[TODO: provide examples of latent issues and potential remediations]
|
59 |
+
|
60 |
+
## Training details
|
61 |
+
|
62 |
+
[TODO: describe the data used to train the model]
|