Instructions to use faaj888/lora with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use faaj888/lora with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline from diffusers.utils import load_image, export_to_video # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("undefined,lkzd7/WAN2.2_LoraSet_NSFW", dtype=torch.bfloat16, device_map="cuda") pipe.load_lora_weights("faaj888/lora") prompt = "TOT" input_image = load_image("https://huggingface.co/datasets/huggingface/documentation-images/resolve/main/diffusers/guitar-man.png") image = pipe(image=input_image, prompt=prompt).frames[0] export_to_video(output, "output.mp4") - Notebooks
- Google Colab
- Kaggle
- Local Apps
- Draw Things
Add lora.safetensors
Browse files- lora.safetensors +3 -0
lora.safetensors
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version https://git-lfs.github.com/spec/v1
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oid sha256:8374eec42a3568d9e1d14f856deebdf1e7302c02e96bb110c5936932d565cca3
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size 129184944
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