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", 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
File size: 1,029 Bytes
f3d279e | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 | [
{
"variant": "original",
"load_seconds": 267.8321040520095,
"load_peak_reserved_mb": 28198.0,
"load_peak_nvidia_mb": 28759,
"cold_request_seconds": 17.904404125991277,
"cold_request_peak_reserved_mb": 34386.0,
"cold_request_peak_nvidia_mb": 35055,
"hot_request_mean_seconds": 17.51234320622623,
"hot_request_max_seconds": 17.781690142001025,
"generation_peak_reserved_mb": 34430.0,
"generation_peak_nvidia_mb": 35099.0,
"generation_gpu_after_max_mb": 35099.0
},
{
"variant": "sdnq",
"load_seconds": 239.45547024699044,
"load_peak_reserved_mb": 14558.0,
"load_peak_nvidia_mb": 15109,
"cold_request_seconds": 18.559326965012588,
"cold_request_peak_reserved_mb": 21588.0,
"cold_request_peak_nvidia_mb": 22259,
"hot_request_mean_seconds": 16.523392025442767,
"hot_request_max_seconds": 16.798510612017708,
"generation_peak_reserved_mb": 21650.0,
"generation_peak_nvidia_mb": 22321.0,
"generation_gpu_after_max_mb": 22321.0
}
]
|