Instructions to use rupeshs/FLUX.1-schnell-openvino-int4 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use rupeshs/FLUX.1-schnell-openvino-int4 with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("rupeshs/FLUX.1-schnell-openvino-int4", 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
- Xet hash:
- 76a168e71d690b43dfa7a9e7c78d98854a602fde5bbfb87f0a0918991c8b4fd0
- Size of remote file:
- 84.6 MB
- SHA256:
- 21265962c088aaa75267679e108aed4ee998d200fb635316fda3afdc459e890f
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