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
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autoencoder/
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βββ __init__.py # Package initialization
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βββ configuration_autoencoder.py
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βββ modeling_autoencoder.py
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βββ register_autoencoder.py
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βββ requirements.txt # Dependencies
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βββ README.md # This file
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```
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## π€ Contributing
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```
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autoencoder/
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βββ __init__.py # Package initialization
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βββ configuration_autoencoder.py # Configuration class
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βββ modeling_autoencoder.py # Model implementations
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βββ register_autoencoder.py # AutoModel registration
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βββ pyproject.toml # Project metadata and dependencies
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βββ README.md # This file
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```
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## π€ Contributing
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