--- tags: - text-to-image - flux - lora - diffusers - template:sd-lora - ai-toolkit widget: - text: a woman wearing a traditional Korean Hanbok, a long-sleeved blouse with intricate embroidery and a high-waisted skirt. The blouse is a deep blue color with a white collar and cuffs, and the skirt is a lighter shade of blue with a pattern of small white flowers. The woman is standing in a graceful pose, her hands clasped in front of her and her head tilted slightly to the side. [trigger] output: url: samples/1729040425975__000001000_0.jpg base_model: black-forest-labs/FLUX.1-dev instance_prompt: hanbok license: other license_name: flux-1-dev-non-commercial-license license_link: https://huggingface.co/black-forest-labs/FLUX.1-dev/blob/main/LICENSE.md --- # hanbok ## Trigger words You should use `hanbok` 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](/seawolf2357/hanbok/tree/main) them in the Files & versions tab. ## Use it with the [🧨 diffusers library](https://github.com/huggingface/diffusers) ```py from diffusers import AutoPipelineForText2Image import torch pipeline = AutoPipelineForText2Image.from_pretrained('black-forest-labs/FLUX.1-dev', torch_dtype=torch.bfloat16).to('cuda') pipeline.load_lora_weights('seawolf2357/hanbok', weight_name='hanbok.safetensors') image = pipeline('a woman wearing a traditional Korean Hanbok, a long-sleeved blouse with intricate embroidery and a high-waisted skirt. The blouse is a deep blue color with a white collar and cuffs, and the skirt is a lighter shade of blue with a pattern of small white flowers. The woman is standing in a graceful pose, her hands clasped in front of her and her head tilted slightly to the side. [trigger]').images[0] image.save("my_image.png") ``` For more details, including weighting, merging and fusing LoRAs, check the [documentation on loading LoRAs in diffusers](https://huggingface.co/docs/diffusers/main/en/using-diffusers/loading_adapters)