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("bzcasper/my_first_lora_v1-lora")
prompt = "[cyberimage]"
image = pipe(prompt).images[0]my_first_lora_v1-lora
Model trained with AI Toolkit by Ostris
Trigger words
You should use [cyberimage] 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.bfloat16).to('cuda')
pipeline.load_lora_weights('bzcasper/my_first_lora_v1-lora', weight_name='my_first_lora_v1_000001000.safetensors')
image = pipeline('[cyberimage]').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 bzcasper/my_first_lora_v1-lora
Base model
Qwen/Qwen-Image