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:
- 61a171d34c50e6a611e457d95474f0f7be7c42502f21c310e482749290f28db5
- Size of remote file:
- 2.61 GB
- SHA256:
- 52181ff0fbb3abee096e5310760c6542782493ecc141735eee6c01e56cc6dad8
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