rootonchair
/

2x2_sticker_sheet

template:diffusion-lora

diffusers-training

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rootonchair commited on 8 days ago

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@@ -56,8 +56,8 @@ 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('rootonchair/4x4_sticker_sheet', weight_name='pytorch_lora_weights.safetensors', adapter_name='4x4_sticker_sheet')
-pipeline.set_adapters(['4x4_sticker_sheet'], adapter_weights=[0.8])
 image = pipeline('This set of four image depicts a cartoon black cat wearing a pirate hat; [IMAGE1] The cat is happy, holding a bouquet; [IMAGE2] The cat is happy, surrounded with music notes; [IMAGE3] The cat is riding a bicycle; [IMAGE4] The cat is eating an ice cream', width=512, height=512, num_inference_steps=28, guidance_scale=3.5).images[0]
 ```

 import torch
 pipeline = AutoPipelineForText2Image.from_pretrained("black-forest-labs/FLUX.1-dev", torch_dtype=torch.bfloat16).to('cuda')
+pipeline.load_lora_weights('rootonchair/2x2_sticker_sheet', weight_name='pytorch_lora_weights.safetensors', adapter_name='2x2_sticker_sheet')
+pipeline.set_adapters(['2x2_sticker_sheet'], adapter_weights=[0.8])
 image = pipeline('This set of four image depicts a cartoon black cat wearing a pirate hat; [IMAGE1] The cat is happy, holding a bouquet; [IMAGE2] The cat is happy, surrounded with music notes; [IMAGE3] The cat is riding a bicycle; [IMAGE4] The cat is eating an ice cream', width=512, height=512, num_inference_steps=28, guidance_scale=3.5).images[0]
 ```