Instructions to use feizhengcong/mochi-1-preview-diffusers with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use feizhengcong/mochi-1-preview-diffusers with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("feizhengcong/mochi-1-preview-diffusers", 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
Upload scheduler_config.json
Browse files
scheduler/scheduler_config.json
CHANGED
|
@@ -3,7 +3,7 @@
|
|
| 3 |
"_diffusers_version": "0.32.0.dev0",
|
| 4 |
"base_image_seq_len": 256,
|
| 5 |
"base_shift": 0.5,
|
| 6 |
-
"invert_sigmas":
|
| 7 |
"max_image_seq_len": 4096,
|
| 8 |
"max_shift": 1.15,
|
| 9 |
"num_train_timesteps": 1000,
|
|
|
|
| 3 |
"_diffusers_version": "0.32.0.dev0",
|
| 4 |
"base_image_seq_len": 256,
|
| 5 |
"base_shift": 0.5,
|
| 6 |
+
"invert_sigmas": true,
|
| 7 |
"max_image_seq_len": 4096,
|
| 8 |
"max_shift": 1.15,
|
| 9 |
"num_train_timesteps": 1000,
|