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:
- 1743574df9954aca2d4a8e36772e41b45191cf3a9becb23340214044cf19cc48
- Size of remote file:
- 13 MB
- SHA256:
- b6df06609476116846ca40b722456034ce9a1d0f93da06c37324eb4e10893a59
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