Instructions to use WALIDALI/lyrieldiff with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use WALIDALI/lyrieldiff with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("WALIDALI/lyrieldiff", 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 Settings
- Draw Things
- DiffusionBee
- Xet hash:
- c2922288d36f8e3a00c95b952d97740f04db5785c3a0856ec8e1ce0017fd307d
- Size of remote file:
- 2.13 GB
- SHA256:
- 347c7c93b25f4ac58faddb20569ba2e400bde33458353a51f6eab2b0075af41e
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