Instructions to use furaidosu/dottv2-qwen-image-lora with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use furaidosu/dottv2-qwen-image-lora with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("Qwen/Qwen-Image", dtype=torch.bfloat16, device_map="cuda") pipe.load_lora_weights("furaidosu/dottv2-qwen-image-lora") prompt = "DOTT style" image = pipe(prompt).images[0] - Inference
- Notebooks
- Google Colab
- Kaggle
- Local Apps
- Draw Things
- DiffusionBee
dottv2 qwen image lora
Model description
Qwen Image LoRA trained on super-resolution snapshots from Day of the Tentacle
Trigger words
You should use DOTT style 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/qwen-image-trainer.
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Model tree for furaidosu/dottv2-qwen-image-lora
Base model
Qwen/Qwen-Image