Text-to-Image
Diffusers
stable-diffusion-xl
sdxl
lora
control
controlnet
control-lora
brightness
grayscale
template:sd-lora
Instructions to use Oysiyl/controlnet-lora-brightness-sdxl with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use Oysiyl/controlnet-lora-brightness-sdxl with Diffusers:
pip install -U diffusers transformers accelerate
from diffusers import ControlNetModel, StableDiffusionControlNetPipeline controlnet = ControlNetModel.from_pretrained("Oysiyl/controlnet-lora-brightness-sdxl") pipe = StableDiffusionControlNetPipeline.from_pretrained( "stabilityai/stable-diffusion-xl-base-1.0", controlnet=controlnet ) - Inference
- Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- Draw Things
- DiffusionBee
Update README: Show scale progression per checkpoint (5 images showing all 7 scales each)
Browse files
README.md
CHANGED
|
@@ -286,25 +286,22 @@ The model includes checkpoints from throughout training:
|
|
| 286 |
|
| 287 |
### Visual Comparison
|
| 288 |
|
| 289 |
-
Each comparison shows QR input + all
|
| 290 |
|
| 291 |
-
####
|
| 292 |
-

|
| 308 |
|
| 309 |
### Key Observations
|
| 310 |
|
|
|
|
| 286 |
|
| 287 |
### Visual Comparison
|
| 288 |
|
| 289 |
+
Each comparison shows QR input + all 7 conditioning scales (0.25, 0.5, 0.7, 0.75, 1.0, 1.25, 1.5) for a specific checkpoint:
|
| 290 |
|
| 291 |
+
#### Checkpoint 78 (25% trained, 2,500 samples)
|
| 292 |
+

|
| 293 |
|
| 294 |
+
#### Checkpoint 156 (50% trained, 5,000 samples)
|
| 295 |
+

|
| 296 |
|
| 297 |
+
#### Checkpoint 234 (75% trained, 7,500 samples)
|
| 298 |
+

|
| 299 |
|
| 300 |
+
#### Checkpoint 312 (99% trained, 9,984 samples)
|
| 301 |
+

|
| 302 |
|
| 303 |
+
#### Final Model (100% trained, 10,000 samples) - Recommended
|
| 304 |
+

|
|
|
|
|
|
|
|
|
|
| 305 |
|
| 306 |
### Key Observations
|
| 307 |
|