Text-to-Image
Diffusers
Safetensors
Ideogram4SDNQPipeline
ideogram
sdnq
uint4
diffusion
typography
8-bit precision
Instructions to use WaveCut/ideogram-4-sdnq-uint4 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use WaveCut/ideogram-4-sdnq-uint4 with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("WaveCut/ideogram-4-sdnq-uint4", torch_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

- Xet hash:
- 664cb57963bc261c113f99dd7b8dbe4c25e248c5e6abab188e752929d77e8c53
- Size of remote file:
- 5.41 MB
- SHA256:
- f7f70232d28ecb1afcfe2691d0b73526102d4aeac2e3ff2f4724cec427e8572f
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.