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 Settings
- Draw Things
- DiffusionBee
- Xet hash:
- ffa4c5beb661339309a893203b81d8491bcae6b018f15a141aa1a293d79ba03e
- Size of remote file:
- 3.49 MB
- SHA256:
- 53861d7f30e7d807e55816e2b4a1058e8dbaaae35539be743900e6cfa9138444
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