Instructions to use xcpan/AnimateDiff-v3-diffusers with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use xcpan/AnimateDiff-v3-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("xcpan/AnimateDiff-v3-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
| { | |
| "_class_name": "MotionAdapter", | |
| "_diffusers_version": "0.22.0.dev0", | |
| "block_out_channels": [ | |
| 320, | |
| 640, | |
| 1280, | |
| 1280 | |
| ], | |
| "motion_activation_fn": "geglu", | |
| "motion_attention_bias": false, | |
| "motion_cross_attention_dim": 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": false | |
| } | |