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license: other |
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--- |
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# This is a Custom Diffusion model fine-tuned from the Stable Diffusion v1-4. |
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Custom Diffusion allows you to fine-tune text-to-image diffusion models, such as Stable Diffusion, given a few images of a new concept (~4-20). |
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Here we give an example model fine-tuned using 5 images of a cat downloaded from UnSplash. The example code of inference is shown below. |
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## Example code of inference |
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```python |
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import os |
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import sys |
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import torch |
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os.system("git clone https://github.com/adobe-research/custom-diffusion") |
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sys.path.append("custom-diffusion") |
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from diffusers import StableDiffusionPipeline |
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from src import diffuser_training |
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device = 'cuda' |
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pipe = StableDiffusionPipeline.from_pretrained(model_id, torch_dtype=torch.float16) |
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pipe = pipe.to(self.device) |
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weight_path = 'custom_diffusion_cat.bin' |
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diffuser_training.load_model(pipe.text_encoder, pipe.tokenizer, pipe.unet, weight_path, '<new1>') |
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prompt = "<new1> cat swimming in a pool" |
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images = pipe(prompt, num_inference_steps=200, guidance_scale=6., eta=1.).images |
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``` |
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