Instructions to use Silan10/flux-quantized-bitsandbytes with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use Silan10/flux-quantized-bitsandbytes with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("Silan10/flux-quantized-bitsandbytes", 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:
- b746a20f79afd93606ccb65150ca1707e0aa88ae4d0b28d8e9de584be7afbae2
- Size of remote file:
- 162 MB
- SHA256:
- 88ad7e2d7c9b83727612daaf410015af3c0e1c37855f41abce6da322f289e6ed
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