Instructions to use vincenthugging/flux-dev-lora-lyf with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use vincenthugging/flux-dev-lora-lyf 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("vincenthugging/flux-dev-lora-lyf") prompt = "a portrait of lyf" image = pipe(prompt).images[0] - Inference
- Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- Draw Things
- DiffusionBee
- Xet hash:
- 7c5695e19bc677013420553d0f2f38d0303aa7761beb247351e147927a33cdc1
- Size of remote file:
- 172 MB
- SHA256:
- 5bf4babc6f6b3211e4913896a238f81a460e599741008a0c508b47ebe5f58c74
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