Instructions to use DAKARA555/test with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use DAKARA555/test with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("stablediffusionapi/wan_lora_v1", dtype=torch.bfloat16, device_map="cuda") pipe.load_lora_weights("DAKARA555/test") prompt = "-" image = pipe(prompt).images[0] - Notebooks
- Google Colab
- Kaggle
- Local Apps
- Draw Things
- DiffusionBee
import torch
from diffusers import DiffusionPipeline
# switch to "mps" for apple devices
pipe = DiffusionPipeline.from_pretrained("stablediffusionapi/wan_lora_v1", dtype=torch.bfloat16, device_map="cuda")
pipe.load_lora_weights("DAKARA555/test")
prompt = "-"
image = pipe(prompt).images[0]test
- Prompt
- -
Model description
test
Download model
Weights for this model are available in Safetensors format.
Download them in the Files & versions tab.
- Downloads last month
- 3
Model tree for DAKARA555/test
Base model
Wan-AI/Wan2.1-T2V-14B-Diffusers Adapter
stablediffusionapi/wan_lora_v1