Feature Extraction
Transformers
Safetensors
PyTorch
autoencoder
reconstruction
preprocessing
normalizing-flow
scaler
custom_code
Instructions to use amaye15/autoencoder with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use amaye15/autoencoder with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("feature-extraction", model="amaye15/autoencoder", trust_remote_code=True)# Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("amaye15/autoencoder", trust_remote_code=True, dtype="auto") - Notebooks
- Google Colab
- Kaggle
| """ | |
| Autoencoder models for Hugging Face Transformers. | |
| """ | |
| from configuration_autoencoder import AutoencoderConfig | |
| from modeling_autoencoder import ( | |
| AutoencoderModel, | |
| AutoencoderForReconstruction, | |
| AutoencoderOutput, | |
| AutoencoderForReconstructionOutput, | |
| ) | |
| __all__ = [ | |
| "AutoencoderConfig", | |
| "AutoencoderModel", | |
| "AutoencoderForReconstruction", | |
| "AutoencoderOutput", | |
| "AutoencoderForReconstructionOutput", | |
| ] | |