Instructions to use YogiBare67/AnimateLCM with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use YogiBare67/AnimateLCM with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("YogiBare67/AnimateLCM", 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
File size: 376 Bytes
58b04f0 | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 | {
"_class_name": "MotionAdapter",
"_diffusers_version": "0.27.0.dev0",
"block_out_channels": [
320,
640,
1280,
1280
],
"conv_in_channels": null,
"motion_layers_per_block": 2,
"motion_max_seq_length": 32,
"motion_mid_block_layers_per_block": 1,
"motion_norm_num_groups": 32,
"motion_num_attention_heads": 8,
"use_motion_mid_block": true
}
|