Instructions to use vladmandic/HiDream-O1-Image-SDNQ-8bit-dynamic with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use vladmandic/HiDream-O1-Image-SDNQ-8bit-dynamic with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("vladmandic/HiDream-O1-Image-SDNQ-8bit-dynamic", 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
Prequantized version of https://huggingface.co/HiDream-ai/HiDream-O1-Image using SDNQ SVD+Dynamic in INT8 precision
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Model tree for vladmandic/HiDream-O1-Image-SDNQ-8bit-dynamic
Base model
HiDream-ai/HiDream-O1-Image