Instructions to use ModelsLab/flux-klein-9b-transformer-fp8 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use ModelsLab/flux-klein-9b-transformer-fp8 with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("ModelsLab/flux-klein-9b-transformer-fp8", 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:
- 597372c56ac2a644f4d60a9fd5af7f206404a88db3cd0b836c68f2fc2cfcf493
- Size of remote file:
- 9.08 GB
- SHA256:
- f84a9459dffef7702f53c15bc8c9dd65f3a05f8b7f287f82bfae4540555d9338
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