Instructions to use dinushiTJ/ift_lora with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use dinushiTJ/ift_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("stabilityai/stable-diffusion-2-1-base", dtype=torch.bfloat16, device_map="cuda") pipe.load_lora_weights("dinushiTJ/ift_lora") prompt = "A <IFT> aerial view" image = pipe(prompt).images[0] - Notebooks
- Google Colab
- Kaggle
- Local Apps
- Draw Things
- DiffusionBee
- Xet hash:
- 6fa824d047f78f941f9e2e0f184cf43e2b34103777920679f9cbf2d4dd1faf53
- Size of remote file:
- 13 MB
- SHA256:
- b14e2bd632bc1c17d73e866c9d42c0cf2ae5f8a253378186c718d0b6d9d76229
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