Instructions to use SimianLuo/LCM_Dreamshaper_v7 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use SimianLuo/LCM_Dreamshaper_v7 with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("SimianLuo/LCM_Dreamshaper_v7", dtype=torch.bfloat16, device_map="cuda") prompt = "Astronaut in a jungle, cold color palette, muted colors, detailed, 8k" image = pipe(prompt).images[0] - Notebooks
- Google Colab
- Kaggle
- Local Apps
- Draw Things
- DiffusionBee
Update scheduler/scheduler_config.json (#14)
Browse files- Update scheduler/scheduler_config.json (0010c37ddd81113174cbde0939e0d703e8b68e9d)
Co-authored-by: Arnaud <agucci@users.noreply.huggingface.co>
scheduler/scheduler_config.json
CHANGED
|
@@ -13,7 +13,7 @@
|
|
| 13 |
"rescale_betas_zero_snr": false,
|
| 14 |
"sample_max_value": 1.0,
|
| 15 |
"set_alpha_to_one": true,
|
| 16 |
-
"steps_offset":
|
| 17 |
"thresholding": false,
|
| 18 |
"timestep_spacing": "leading",
|
| 19 |
"trained_betas": null
|
|
|
|
| 13 |
"rescale_betas_zero_snr": false,
|
| 14 |
"sample_max_value": 1.0,
|
| 15 |
"set_alpha_to_one": true,
|
| 16 |
+
"steps_offset": 1,
|
| 17 |
"thresholding": false,
|
| 18 |
"timestep_spacing": "leading",
|
| 19 |
"trained_betas": null
|