Instructions to use Tongyi-MAI/Z-Image-Turbo with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use Tongyi-MAI/Z-Image-Turbo with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("Tongyi-MAI/Z-Image-Turbo", dtype=torch.bfloat16, device_map="cuda") prompt = "Astronaut in a jungle, cold color palette, muted colors, detailed, 8k" image = pipe(prompt).images[0] - Inference
- Notebooks
- Google Colab
- Kaggle
- AMD Developer Cloud
- Local Apps Settings
- Draw Things
- DiffusionBee
Upload scheduler_config.json
Browse files
scheduler/scheduler_config.json
CHANGED
|
@@ -1,18 +1,7 @@
|
|
| 1 |
-
{
|
| 2 |
-
"_class_name": "FlowMatchEulerDiscreteScheduler",
|
| 3 |
-
"_diffusers_version": "0.36.0.dev0",
|
| 4 |
-
"
|
| 5 |
-
"
|
| 6 |
-
"
|
| 7 |
-
|
| 8 |
-
"max_shift": 1.15,
|
| 9 |
-
"num_train_timesteps": 1000,
|
| 10 |
-
"shift": 3.0,
|
| 11 |
-
"shift_terminal": null,
|
| 12 |
-
"stochastic_sampling": false,
|
| 13 |
-
"time_shift_type": "exponential",
|
| 14 |
-
"use_beta_sigmas": false,
|
| 15 |
-
"use_dynamic_shifting": false,
|
| 16 |
-
"use_exponential_sigmas": false,
|
| 17 |
-
"use_karras_sigmas": false
|
| 18 |
-
}
|
|
|
|
| 1 |
+
{
|
| 2 |
+
"_class_name": "FlowMatchEulerDiscreteScheduler",
|
| 3 |
+
"_diffusers_version": "0.36.0.dev0",
|
| 4 |
+
"num_train_timesteps": 1000,
|
| 5 |
+
"use_dynamic_shifting": false,
|
| 6 |
+
"shift": 3.0
|
| 7 |
+
}
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|