Instructions to use yanxg/FLUX.1-Kontext-dev-custom-TrimS with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use yanxg/FLUX.1-Kontext-dev-custom-TrimS with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("yanxg/FLUX.1-Kontext-dev-custom-TrimS", 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:
- 10a48fc6e86a62204538212cb2fd8b07bead57d6ced55225d95469678fc41e03
- Size of remote file:
- 5.2 GB
- SHA256:
- 4b9dbe487498498a972d15236ffbf6eda9f0e0a8f9ac2dff2d9ff46774962397
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