Text-to-Image
Diffusers
lora
diffusers-training
stable-diffusion
stable-diffusion-diffusers
template:sd-lora
stable-diffusion-xl
stable-diffusion-xl-diffusers
Instructions to use kfkas/test_lora_dreambooth_v2 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use kfkas/test_lora_dreambooth_v2 with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("CompVis/stable-diffusion-v1-4", dtype=torch.bfloat16, device_map="cuda") pipe.load_lora_weights("kfkas/test_lora_dreambooth_v2") prompt = "a photo of Korea sks Sungnyemun Gate" image = pipe(prompt).images[0] - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- Draw Things
- DiffusionBee
End of training
Browse files- .gitattributes +2 -0
- README.md +8 -0
- checkpoint-1000/optimizer.bin +2 -2
- checkpoint-1000/pytorch_lora_weights.safetensors +2 -2
- checkpoint-1000/random_states_0.pkl +2 -2
- checkpoint-1000/scheduler.bin +2 -2
- checkpoint-500/optimizer.bin +2 -2
- checkpoint-500/pytorch_lora_weights.safetensors +2 -2
- checkpoint-500/random_states_0.pkl +2 -2
- checkpoint-500/scheduler.bin +2 -2
- image_0.png +0 -0
- image_1.png +0 -0
- image_2.png +0 -0
- image_3.png +0 -0
- pytorch_lora_weights.safetensors +2 -2
.gitattributes
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README.md
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- diffusers-training
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---
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<!-- This model card has been generated automatically according to the information the training script had access to. You
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- diffusers-training
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---
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<!-- This model card has been generated automatically according to the information the training script had access to. You
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