Instructions to use KLOWNZone23/lora with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use KLOWNZone23/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("KLOWNZone23/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
metadata
tags:
- flux
- text-to-image
- lora
- diffusers
- fal
base_model:
- undefined
- lkzd7/WAN2.2_LoraSet_NSFW
instance_prompt: TOT
license: other
datasets:
- mess2735/wan2.2_lora
language:
- en
metrics:
- character
new_version: lkzd7/WAN2.2_LoraSet_NSFW
pipeline_tag: image-to-video
library_name: diffusers
lora
Model description
My lora model
Trigger words
You should use TOT to trigger the image generation.
Download model
Weights for this model are available in Safetensors format.
Download them in the Files & versions tab.
Training at fal.ai
Training was done using fal.ai/models/fal-ai/turbo-flux-trainer.