--- tags: - text-to-image - stable-diffusion - lora - diffusers - image-generation - flux - safetensors widget: - text: >- A young man, gold hair, white T-shirt. The background is 4 real photos, and in the middle is a cartoon picture summarizing the real photos. output: url: images/b4425607370dcaa80717519f157a64436dd92238dc60786639845551.jpg - text: >- A panda.The background is 4 real photos, and in the middle is a cartoon picture summarizing the real photos. output: url: images/f2cc649985648e57b9b9b14ca7a8744ac8e50d75b3a334ed4df0f368.jpg - text: >- A young girl, red hair, blue dress. The background is 4 real photos, and in the middle is a cartoon picture summarizing the real photos. output: url: images/9104a1e9c1debdb1188c06a5e07bf4a084f0d8005e082f01f8de7c19.jpg base_model: black-forest-labs/FLUX.1-dev instance_prompt: >- The background is 4 real photos, and in the middle is a cartoon picture summarizing the real photos 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 language: - en library_name: diffusers --- # FLUX.1-dev-LoRA-One-Click-Creative-Template This is a LoRA trained on FLUX.1-dev by [Nvwa_model_studio](https://www.shakker.ai/userpage/cd65d71ff6a74bbfaaeba0b898dbf856/publish) for creative photos.
## Showcases ## Trigger words You should use `The background is 4 real photos, and in the middle is a cartoon picture summarizing the real photos.` to trigger the image generation. The recommended scale is `1.0` in diffusers. ## Inference ```python import torch from diffusers import FluxPipeline pipe = FluxPipeline.from_pretrained("black-forest-labs/FLUX.1-dev", torch_dtype=torch.bfloat16) pipe.load_lora_weights("Shakker-Labs/FLUX.1-dev-LoRA-One-Click-Creative-Template", weight_name="FLUX-dev-lora-One-Click-Creative-Template.safetensors") pipe.fuse_lora(lora_scale=1.0) pipe.to("cuda") prompt = "A young girl, red hair, blue dress. The background is 4 real photos, and in the middle is a cartoon picture summarizing the real photos." image = pipe(prompt, num_inference_steps=24, guidance_scale=3.5, width=960, height=1280, ).images[0] image.save(f"example.png") ``` ## Online Inference You can also download this model at [Shakker AI](https://www.shakker.ai/modelinfo/16681dcf76e7447a83731c02eb4f4efe?from=personal_page), where we provide an online interface to generate images. ## Acknowledgements This model is trained by our copyrighted users [Nvwa_model_studio](https://www.shakker.ai/userpage/cd65d71ff6a74bbfaaeba0b898dbf856/publish). We release this model under permissions.