Instructions to use ermanmanyasli/kobet with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use ermanmanyasli/kobet with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("black-forest-labs/FLUX.1-dev", dtype=torch.bfloat16, device_map="cuda") pipe.load_lora_weights("ermanmanyasli/kobet") prompt = "y1nu5" image = pipe(prompt).images[0] - Inference
- Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- Draw Things
- DiffusionBee
- Xet hash:
- 56d13de7adb287c7e696ebc5d9b4fa09b75678096396fa0f53ab1c3035a32192
- Size of remote file:
- 173 MB
- SHA256:
- 8035b5f7c48b6000fb3682e51fba95e078d61d9e12e48c28629974b6003f2764
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