Instructions to use CodeGoat24/FLUX.2-klein-base-9B-UnifiedReward-Flex-lora with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use CodeGoat24/FLUX.2-klein-base-9B-UnifiedReward-Flex-lora with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("CodeGoat24/FLUX.2-klein-base-9B-UnifiedReward-Flex-lora", 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:
- ae335015e3103ebb9b36a3b4ecd380dc7df49a4568f335d31ad2971be4949ffe
- Size of remote file:
- 1.14 GB
- SHA256:
- c564b995c57f86fea7aa7819c34346b008ed8cb4bb2cb154e70f4ce2a0ac354f
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