Instructions to use zecloud/mechas with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use zecloud/mechas with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("zecloud/mechas", 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 README.md
Browse files
README.md
CHANGED
|
@@ -11,7 +11,7 @@ from diffusers.utils import export_to_gif
|
|
| 11 |
# Load the motion adapter
|
| 12 |
adapter = MotionAdapter.from_pretrained("guoyww/animatediff-motion-adapter-v1-5-2", torch_dtype=torch.float16)
|
| 13 |
# load SD 1.5 based finetuned model
|
| 14 |
-
model_id = "
|
| 15 |
pipe = AnimateDiffPipeline.from_pretrained(model_id, motion_adapter=adapter, torch_dtype=torch.float16)
|
| 16 |
scheduler = DDIMScheduler.from_pretrained(
|
| 17 |
model_id,
|
|
|
|
| 11 |
# Load the motion adapter
|
| 12 |
adapter = MotionAdapter.from_pretrained("guoyww/animatediff-motion-adapter-v1-5-2", torch_dtype=torch.float16)
|
| 13 |
# load SD 1.5 based finetuned model
|
| 14 |
+
model_id = "zecloud/mechas"
|
| 15 |
pipe = AnimateDiffPipeline.from_pretrained(model_id, motion_adapter=adapter, torch_dtype=torch.float16)
|
| 16 |
scheduler = DDIMScheduler.from_pretrained(
|
| 17 |
model_id,
|