Instructions to use Gamahea/LEMM-models with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use Gamahea/LEMM-models with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("Gamahea/LEMM-models", 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
- Xet hash:
- 132f4ee19a98d15a1dc5617780fbceb403eda16859a9ddf20fc7e59484393bf4
- Size of remote file:
- 314 MB
- SHA256:
- 2b0cb469307ac50659d1880db2a99bae47d0df335cbb36853964662d4b80e8ee
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