Instructions to use vidfom/Wan-T2V_14B with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use vidfom/Wan-T2V_14B with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("vidfom/Wan-T2V_14B", 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
Download DiffSynth-Studio/diffsynth/processors/PILEditor.py from vidfom/Wan-T2V_14B: direct link, hf CLI and curl.
- Browser
- Download file 855 Bytes
-
https://huggingface.co/vidfom/Wan-T2V_14B/resolve/main/DiffSynth-Studio/diffsynth/processors/PILEditor.py
- Command line
-
hf download hf://vidfom/Wan-T2V_14B/DiffSynth-Studio/diffsynth/processors/PILEditor.py
-
curl -L -o PILEditor.py https://huggingface.co/vidfom/Wan-T2V_14B/resolve/main/DiffSynth-Studio/diffsynth/processors/PILEditor.py
855 Bytes
| from PIL import ImageEnhance | |
| from .base import VideoProcessor | |
| class ContrastEditor(VideoProcessor): | |
| def __init__(self, rate=1.5): | |
| self.rate = rate | |
| def from_model_manager(model_manager, **kwargs): | |
| return ContrastEditor(**kwargs) | |
| def __call__(self, rendered_frames, **kwargs): | |
| rendered_frames = [ImageEnhance.Contrast(i).enhance(self.rate) for i in rendered_frames] | |
| return rendered_frames | |
| class SharpnessEditor(VideoProcessor): | |
| def __init__(self, rate=1.5): | |
| self.rate = rate | |
| def from_model_manager(model_manager, **kwargs): | |
| return SharpnessEditor(**kwargs) | |
| def __call__(self, rendered_frames, **kwargs): | |
| rendered_frames = [ImageEnhance.Sharpness(i).enhance(self.rate) for i in rendered_frames] | |
| return rendered_frames | |