Instructions to use amaye15/autoencoder-robust-demo with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use amaye15/autoencoder-robust-demo with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("feature-extraction", model="amaye15/autoencoder-robust-demo", trust_remote_code=True)# Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("amaye15/autoencoder-robust-demo", trust_remote_code=True, dtype="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- ca9e57ca2d22ef84b603866ac2cb5cccc26809d6f60e210c519f2828f811a2ea
- Size of remote file:
- 5.78 kB
- SHA256:
- 14e56e5ad0c4b49490b81fd03efb444c425ac02e5b4a9dc8cb26ecb1764b2c3d
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