Text-to-Image
Diffusers
Safetensors
StableDiffusion3Pipeline
diffusers-training
template:sd-lora
sd3
sd3-diffusers
Instructions to use jatr96/trained-sd3 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use jatr96/trained-sd3 with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("jatr96/trained-sd3", dtype=torch.bfloat16, device_map="cuda") prompt = "A photo of sks dog in a bucket" image = pipe(prompt).images[0] - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- Draw Things
- DiffusionBee

- Xet hash:
- c2dc9e610f184af6f0bd21f7f182f76d4a975d55f22ad6cf271c1cfdcc099331
- Size of remote file:
- 1.57 MB
- SHA256:
- 99c9ac007ffa362d4f36df418e8a9ec838827572fbc7a377991634aeabb58756
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.