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, device_map="auto") - Notebooks
- Google Colab
- Kaggle
File size: 439 Bytes
ced6e93 | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 | """
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",
]
|