    >>> import torch
    >>> from diffusers import QwenImagePipeline

    >>> pipe = QwenImagePipeline.from_pretrained(
    ...     "Qwen/Qwen-Image",
    ...     torch_dtype=torch.bfloat16,
    ... )
    >>> pipe.enable_model_cpu_offload()
    >>> pipe.load_lora_weights(f"viyer7/trained-qwen-lora_5500_1024steps")
    >>> image = pipe(f"None").images[0]

For more details, including weighting, merging and fusing LoRAs, check the documentation on loading LoRAs in diffusers

Intended uses & limitations

How to use

# TODO: add an example code snippet for running this diffusion pipeline

Limitations and bias

[TODO: provide examples of latent issues and potential remediations]

Training details

[TODO: describe the data used to train the model]