Instructions to use EcoCy/jultest with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use EcoCy/jultest 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("EcoCy/jultest") prompt = "jultest01" image = pipe(prompt).images[0] - Notebooks
- Google Colab
- Kaggle
- Local Apps
- Draw Things
- DiffusionBee
- Xet hash:
- 4f6efddb91243be2968da13e32fd5e095d0c1873a93909d82f514a9467a1cdbe
- Size of remote file:
- 3.42 MB
- SHA256:
- b7b719d1976b623d735064f861be606c25d7c8d489849da64c8187d9a13f724b
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