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:
- 79c7c6894dfe39c8469051e9d017da1a318dbae8c10bf03caa40d478b26a8376
- Size of remote file:
- 13 MB
- SHA256:
- 492f640ce1e2ef4a2d0d4d9343a7ab5ed7facde262ba38033e0c73e769ad4c6d
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