Instructions to use furaidosu/tosti-qwen-image-lora with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use furaidosu/tosti-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/tosti-qwen-image-lora") prompt = "and anthropomorphic cockroach bodyguard wearing black tuxedo and red ties. The cockroach is wearing black eyeglasses. deep Blue background" image = pipe(prompt).images[0] - Inference
- Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- Draw Things
- DiffusionBee
- Xet hash:
- b5e3c5d777a7b0de17be23c52876df816dcffb6c4b5c100b146f8a8b89e0c385
- Size of remote file:
- 590 MB
- SHA256:
- b13d9fdd647d7622cec2d7936c329c61adf2621e6e2486ba8556b6d87962a8bf
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.