Text-to-Image
Diffusers
Safetensors
StableDiffusion3Pipeline
diffusers-training
template:sd-lora
sd3
sd3-diffusers
Instructions to use dashabalashova/trained-sd3 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use dashabalashova/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("dashabalashova/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:
- 8b7126baa744ec2a37fcb15fa9e31d5c237ee145d66ff9db87cc3e6c1a5998ca
- Size of remote file:
- 14.8 kB
- SHA256:
- c862e450aceaf57bc26e398bf3fd076e1f30cff2d407f2a6fef4a69aff652d07
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.