Instructions to use kyn27/wavespeed_clover_lora with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use kyn27/wavespeed_clover_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("kyn27/wavespeed_clover_lora") prompt = "v" image = pipe(prompt).images[0] - Inference
- Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- Draw Things
- DiffusionBee
metadata
tags:
- text-to-image
- lora
- diffusers
- template:diffusion-lora
widget:
- output:
url: images/high_fidelity_00003_.png
text: v
parameters:
negative_prompt: va
base_model: Qwen/Qwen-Image
instance_prompt: c0denameCloverV2
license: apache-2.0
wavespeed lora 1

- Prompt
- v
- Negative Prompt
- va
Model description
c0denameCloverV2
Trigger words
You should use c0denameCloverV2 to trigger the image generation.
Download model
Download them in the Files & versions tab.