Instructions to use minyeol/loramergetestmodel with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use minyeol/loramergetestmodel with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("minyeol/loramergetestmodel", dtype=torch.bfloat16, device_map="cuda") prompt = "Astronaut in a jungle, cold color palette, muted colors, detailed, 8k" image = pipe(prompt).images[0] - Notebooks
- Google Colab
- Kaggle
- Local Apps
- Draw Things
- DiffusionBee
- Xet hash:
- 7b16ff32121318f9bcc71829f7f698b2eb98af5e8e463aac940b8361e8ab619c
- Size of remote file:
- 492 MB
- SHA256:
- 38dac0a54c1c166a40d8bc0510cec482903d89e92c3d40ab8466160b11f399a1
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