Instructions to use HReynaud/EchoNet-Synthetic with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use HReynaud/EchoNet-Synthetic with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("HReynaud/EchoNet-Synthetic", 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:
- 78be9c18b835ed02a5b7144a0160f1ec8f6d23fdcf8dad994cbf0a5fc5523a6b
- Size of remote file:
- 250 MB
- SHA256:
- ba0be1555511d1e145bfda156062aab744c6f7fc12e930c78c3640baf8183d5b
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