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)# pip install -U transformers accelerate # Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("amaye15/autoencoder-robust-demo", trust_remote_code=True, device_map="auto") - Notebooks
- Google Colab
- Kaggle
Commit History
-
Update modeling_autoencoder.py to support relative import for HF dynamic modules
Verified signature767a789 -
Update configuration_autoencoder.py to support relative import for HF dynamic modules
Verified signature1afcb0c -
Model save
Verified signature7bd2310 -
Training in progress, epoch 1
Verified signaturefabf416 -
initial commit
Verified signature85501fc