Instructions to use quarterturn/wan2.2-14b-t2v-watamote with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use quarterturn/wan2.2-14b-t2v-watamote with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline from diffusers.utils import export_to_video # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("Wan-AI/Wan2.2-T2V-14B", dtype=torch.bfloat16, device_map="cuda") pipe.load_lora_weights("quarterturn/wan2.2-14b-t2v-watamote") prompt = "A man with short gray hair plays a red electric guitar." output = pipe(prompt=prompt).frames[0] export_to_video(output, "output.mp4") - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- Draw Things
A Wan 2.2 14B t2v LoRA for Watamote/Kuroki Tomoko.
This is a preliminary release. I may decide to train it further. It does not seem to work well in conjuction with lightning or similar speedup LoRAs.
Trained on 270 1280x720 images using diffusion-pipe for 35 epochs as rank 32.
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