Instructions to use wouterverweirder/wan_2_2_5B_woven_fabric_02-lora with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use wouterverweirder/wan_2_2_5B_woven_fabric_02-lora 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-TI2V-5B-Diffusers", torch_dtype=torch.bfloat16, device_map="cuda") pipe.load_lora_weights("wouterverweirder/wan_2_2_5B_woven_fabric_02-lora") prompt = "w0v3nf4br1c" output = pipe(prompt=prompt).frames[0] export_to_video(output, "output.mp4") - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- Draw Things
wan_2_2_5B_woven_fabric_02-lora
Model trained with AI Toolkit by Ostris
Trigger words
You should use w0v3nf4br1c to trigger the image generation.
Download model and use it with ComfyUI, AUTOMATIC1111, SD.Next, Invoke AI, etc.
Weights for this model are available in Safetensors format.
Download them in the Files & versions tab.
Use it with the 🧨 diffusers library
from diffusers import AutoPipelineForText2Image
import torch
pipeline = AutoPipelineForText2Image.from_pretrained('Wan-AI/Wan2.2-TI2V-5B-Diffusers', torch_dtype=torch.bfloat16).to('cuda')
pipeline.load_lora_weights('wouterverweirder/wan_2_2_5B_woven_fabric_02-lora', weight_name='wan_2_2_5B_woven_fabric_02_000004000.safetensors')
image = pipeline('w0v3nf4br1c').images[0]
image.save("my_image.png")
For more details, including weighting, merging and fusing LoRAs, check the documentation on loading LoRAs in diffusers
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Model tree for wouterverweirder/wan_2_2_5B_woven_fabric_02-lora
Base model
Wan-AI/Wan2.2-TI2V-5B-Diffusers