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:
- 3b4d734f1db1e9a6aee44e250a04b57780e164248a165da15f6738029ca33d9d
- Size of remote file:
- 495 MB
- SHA256:
- fab2e9f2a5d3d8822ebd40a4f0ad22d5119dde950b31f8922c3e8d5622704a1c
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.