Text-to-Image
Diffusers
stable-diffusion-xl
stable-diffusion-xl-diffusers
diffusers-training
lora
template:sd-lora
Instructions to use Cicistawberry/y2k-lora with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use Cicistawberry/y2k-lora 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-xl-base-1.0", dtype=torch.bfloat16, device_map="cuda") pipe.load_lora_weights("Cicistawberry/y2k-lora") prompt = "A <s0><s1> ad, Coca-Cola" image = pipe(prompt).images[0] - Inference
- Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- Draw Things
- DiffusionBee
End of training
Browse files- y2k-v2.safetensors +3 -0
y2k-v2.safetensors
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version https://git-lfs.github.com/spec/v1
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oid sha256:9f2599d99745284cfe0cc9022ac3b26270121f97ea0d34807920b22a027d517f
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size 186046568
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