Instructions to use RishubhPar/trained-sd3-lora with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use RishubhPar/trained-sd3-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-3-medium-diffusers", dtype=torch.bfloat16, device_map="cuda") pipe.load_lora_weights("RishubhPar/trained-sd3-lora") prompt = "A photo of sks dog in a bucket" image = pipe(prompt).images[0] - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- Draw Things
- DiffusionBee
File size: 129 Bytes
8e79600 | 1 2 3 4 | version https://git-lfs.github.com/spec/v1
oid sha256:55d89757e9a416b80d2e21ab8e682105c317c618793a364358277d485b3dbfc8
size 1000
|