Instructions to use Esdolo/FreeVS_WOD with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use Esdolo/FreeVS_WOD with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("Esdolo/FreeVS_WOD", 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": "StableVideoDiffusionPipeline_convnb", | |
| "_diffusers_version": "0.28.0.dev0", | |
| "feature_extractor": [ | |
| "transformers", | |
| "CLIPImageProcessor" | |
| ], | |
| "image_encoder": [ | |
| "transformers", | |
| "CLIPVisionModelWithProjection" | |
| ], | |
| "layout_encoder": [ | |
| "src.encoder.unified_encoder", | |
| "LayoutCondEncoder" | |
| ], | |
| "scheduler": [ | |
| "diffusers", | |
| "EulerDiscreteScheduler" | |
| ], | |
| "unet": [ | |
| "src.model.unet_spatial_temporal_condition_custom", | |
| "UNetSpatioTemporalConditionModelV2" | |
| ], | |
| "vae": [ | |
| "diffusers", | |
| "AutoencoderKLTemporalDecoder" | |
| ] | |
| } | |