Instructions to use xreborn/ohwx2_wan-lora with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use xreborn/ohwx2_wan-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("ai-toolkit/Wan2.2-T2V-A14B-Diffusers-bf16", dtype=torch.bfloat16, device_map="cuda") pipe.load_lora_weights("xreborn/ohwx2_wan-lora") prompt = "ohwx girl" output = pipe(prompt=prompt).frames[0] export_to_video(output, "output.mp4") - Notebooks
- Google Colab
- Kaggle
- Local Apps
- Draw Things
ohwx2_wan-lora
Model trained with AI Toolkit by Ostris
Trigger words
You should use ohwx girl 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('ai-toolkit/Wan2.2-T2V-A14B-Diffusers-bf16', torch_dtype=torch.bfloat16).to('cuda')
pipeline.load_lora_weights('xreborn/ohwx2_wan-lora', weight_name='ohwx2_wan_low_noise.safetensors')
image = pipeline('ohwx girl').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 xreborn/ohwx2_wan-lora
Base model
ai-toolkit/Wan2.2-T2V-A14B-Diffusers-bf16