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--- |
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license: creativeml-openrail-m |
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base_model: stabilityai/stable-diffusion-2 |
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tags: |
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- stable-diffusion |
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- stable-diffusion-diffusers |
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- text-to-image |
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- diffusers |
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- lora |
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inference: true |
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datasets: |
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- hahminlew/kream-product-blip-captions |
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language: |
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- en |
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library_name: diffusers |
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--- |
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# LoRA text2image fine-tuning - NouRed/sd-fashion-products |
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These are LoRA adaption weights for stabilityai/stable-diffusion-2. The weights were fine-tuned on the hahminlew/kream-product-blip-captions dataset. You can find some example images in the following. |
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![img_0](./image_0.jpg) |
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![img_1](./image_1.jpg) |
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![img_2](./image_2.jpg) |
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![img_3](./image_3.jpg) |
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## Usage |
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```python |
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import torch |
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from diffusers import DiffusionPipeline |
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# Load Previous Pipeline |
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pipeline = DiffusionPipeline.from_pretrained( |
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"stabilityai/stable-diffusion-2", revision=None, variant=None, torch_dtype=torch_dtype=torch.float32 |
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) |
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pipeline = pipeline.to(accelerator.device) |
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# Load attention processors |
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pipeline.unet.load_attn_procs("NouRed/sd-fashion-products") |
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# Run Inference |
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generator = torch.Generator(device=accelerator.device) |
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seed = 42 |
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if seed is not None: |
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generator = generator.manual_seed(seed) |
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prompt = "outer, The North Face x Supreme White Label Nuptse Down Jacket Cream, a photography of a white puffer jacket with a red box logo on the front." |
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image = pipeline(prompt, num_inference_steps=30, generator=generator).images[0] |
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# Save Generated Product |
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image.save("red_box_jacket.png") |
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``` |