Text-to-Image
Diffusers
Chinese
AltDiffusionPipeline
stable-diffusion
stable-diffusion-diffusers
multilingual
English(En)
Chinese(Zh)
Spanish(Es)
French(Fr)
Russian(Ru)
Japanese(Ja)
Korean(Ko)
Arabic(Ar)
Italian(It)
Instructions to use BAAI/AltDiffusion-m9 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use BAAI/AltDiffusion-m9 with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("BAAI/AltDiffusion-m9", 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
- Draw Things
- DiffusionBee
- Xet hash:
- 17b511cc036c9029407c3b1b3bdb0854871b6f15b58ea7cc77442609d67b0664
- Size of remote file:
- 2.24 GB
- SHA256:
- ad6a194d6e623a46a7aa5cfeba8a00b1b9920b4a3550bcf9323467ee59919a97
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.