Text-to-Image
Diffusers
Safetensors
French
StableDiffusionPipeline
stable-diffusion
stable-diffusion-diffusers
Instructions to use Acadys/PointConImageModel with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use Acadys/PointConImageModel with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("Acadys/PointConImageModel", 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:
- 36d4ba1d4268d0a74c2733d3c91092db2560eb890ea00411912a5200cce4f3e6
- Size of remote file:
- 6.88 GB
- SHA256:
- 5e325bbaac4ab436cd2678ba330c3d5e8f0360571e93a6120e101d8cdbcf0904
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.