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("PakNin/chao-hu")
prompt = "巢湖、渔船、渔民撒网"
image = pipe(prompt).images[0]chao-hu
Model trained with AI Toolkit by Ostris
- Prompt
- 巢湖、渔船、渔民撒网
- Prompt
- 巢湖、渔船、渔民撒网、國畫風
- Prompt
- 巢湖、渔船、渔民撒网、两岸青山、裕溪河田园山景
Trigger words
You should use 巢湖 to trigger the image generation.
Download model and use it with ComfyUI, AUTOMATIC1111, SD.Next, Invoke AI, etc.
Weights for this model are available in Safetensors format.
Download them in the Files & versions tab.
Use it with the 🧨 diffusers library
from diffusers import AutoPipelineForText2Image
import torch
pipeline = AutoPipelineForText2Image.from_pretrained('Qwen/Qwen-Image', torch_dtype=torch.float16).to('cuda')
pipeline.load_lora_weights('PakNin/chao-hu', weight_name='chao-hu.safetensors')
image = pipeline('巢湖、渔船、渔民撒网').images[0]
image.save("my_image.png")
For more details, including weighting, merging and fusing LoRAs, check the documentation on loading LoRAs in diffusers
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Model tree for PakNin/chao-hu
Base model
Qwen/Qwen-Image