Instructions to use kashif/EfficientNetEncoder with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use kashif/EfficientNetEncoder with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("kashif/EfficientNetEncoder", 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
Download diffusion_pytorch_model.safetensors from kashif/EfficientNetEncoder: direct link, hf CLI and curl.
- Browser
- Download file 81.5 MB
-
https://huggingface.co/kashif/EfficientNetEncoder/resolve/main/diffusion_pytorch_model.safetensors
- Command line
-
hf download hf://kashif/EfficientNetEncoder/diffusion_pytorch_model.safetensors
-
curl -L -o diffusion_pytorch_model.safetensors https://huggingface.co/kashif/EfficientNetEncoder/resolve/main/diffusion_pytorch_model.safetensors
81.5 MB
- Xet hash:
- 07601205ba7bb384b6fe1747de6c1e98b3cf6c7646867ba35acc1059ed8cb731
- Size of remote file:
- 81.5 MB
- SHA256:
- 940911290fc1d34e8e26941e7f37ba477b7abfd004aa25e78b5fd0bf0b3cd599
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