Instructions to use jyp96/fancy_boot with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use jyp96/fancy_boot with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("stabilityai/stable-diffusion-3-medium-diffusers", dtype=torch.bfloat16, device_map="cuda") pipe.load_lora_weights("jyp96/fancy_boot") prompt = "A photo of sks fancy_boot in a bucket" image = pipe(prompt).images[0] - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- Draw Things
- DiffusionBee
End of training
Browse files- checkpoint-100/optimizer.bin +1 -1
- checkpoint-100/pytorch_lora_weights.safetensors +1 -1
- checkpoint-100/scheduler.bin +1 -1
- checkpoint-200/optimizer.bin +1 -1
- checkpoint-200/pytorch_lora_weights.safetensors +1 -1
- checkpoint-200/scheduler.bin +1 -1
- checkpoint-300/optimizer.bin +1 -1
- checkpoint-300/pytorch_lora_weights.safetensors +1 -1
- checkpoint-300/scheduler.bin +1 -1
- checkpoint-400/optimizer.bin +1 -1
- checkpoint-400/pytorch_lora_weights.safetensors +1 -1
- checkpoint-400/scheduler.bin +1 -1
- checkpoint-500/optimizer.bin +1 -1
- checkpoint-500/pytorch_lora_weights.safetensors +1 -1
- checkpoint-500/scheduler.bin +1 -1
- image_0.png +2 -2
- image_1.png +2 -2
- image_2.png +2 -2
- image_3.png +2 -2
- pytorch_lora_weights.safetensors +1 -1
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