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:
- c32506b45ce148ee9d1c339e4628c1116249f5cb1fd15b0f5186834bfbe24b31
- Size of remote file:
- 3.49 MB
- SHA256:
- cb456d15cf1886362ec39c1d813cfffdca17e7a9f6f61940b1e39eb95bea880a
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