Instructions to use satani/lils-2 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use satani/lils-2 with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("satani/lils-2", 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:
- a8403a5d69a7187050e6704ed4a433d5ffdabbc606aa907f13f5487b52470fe9
- Size of remote file:
- 335 MB
- SHA256:
- 6d9f473a3fb66fa29faa1cfb7a0edcedf610adc119493239fd08df964d309ba2
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