Instructions to use davidlorincz/devid with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use davidlorincz/devid 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("davidlorincz/devid") prompt = "DEVID" image = pipe(prompt).images[0] - Inference
- Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- Draw Things
- DiffusionBee
- Xet hash:
- f7f2817ff0d62337d8a9aba512afaf014128ab6346fe0fe866d59a569bf49baa
- Size of remote file:
- 172 MB
- SHA256:
- 00579bbffb8a50d1590d350b52ed280f518fc3eb831e6d57e8aa475483ea5f83
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