Text-to-Image
Diffusers
Safetensors
StableDiffusionXLPipeline
ultra-realistic
stable-diffusion
distilled-model
knowledge-distillation
Instructions to use segmind/SSD-1B with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use segmind/SSD-1B with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("segmind/SSD-1B", dtype=torch.bfloat16, device_map="cuda") prompt = "Astronaut in a jungle, cold color palette, muted colors, detailed, 8k" image = pipe(prompt).images[0] - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- Draw Things
- DiffusionBee
can add normal fp32 model weights to unet,vae,text_encoders
#1
by danielthx - opened
can add normal fp32 model weights like unet,vae,text_encoders..etc. So that can use diffuser training scripts?
danielthx changed discussion title from can add normal fp32 model weights like unet,vae,text_encoders to can add normal fp32 model weights to unet,vae,text_encoders
Icar changed discussion status to closed