import torch
from diffusers import DiffusionPipeline
# switch to "mps" for apple devices
pipe = DiffusionPipeline.from_pretrained("fill-in-base-model", dtype=torch.bfloat16, device_map="cuda")
pipe.load_lora_weights("RobertLau/lora_dreambooth_example")
prompt = "a photo of <|tiaowu|> boy"
image = pipe(prompt).images[0]YAML Metadata Error:"base_model" with value "/mnt/public_cv_model_checkpoints/anything-v3.0/" is not valid. Use a model id from https://hf.co/models.
LoRA DreamBooth - RobertLau/lora_dreambooth_example
These are LoRA adaption weights for /mnt/public_cv_model_checkpoints/anything-v3.0/. The weights were trained on a photo of <|tiaowu|> boy using DreamBooth. You can find some example images in the following.
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