ASTRA: Model Checkpoints & ONNX Exports

This repository hosts the pre-trained and fine-tuned model weights for the ASTRA (Attention-based Self-supervised Time-series Representation Architecture) framework. It includes the original TensorFlow/Keras model weights as well as optimized ONNX formats designed for lightweight production inference.


🌐 The ASTRA Ecosystem

The ASTRA project is split across four distinct repositories:

Repository Description Link
Development Code Core framework, data pipeline, and model training. GitHub: astra
Inference Code Lightweight, production-ready inference scripts and utilities. GitHub: astra-infer
Astronomy Dataset Light curve datasets formatted for ASTRA. Hugging Face: Dataset
Model Weights & ONNX Pre-trained & finetuned model checkpoints along with ONNX exports (This Repo). [Current Repository]

πŸ“‚ Repository File Structure

The model weights in this repository are organized as follows:

β”œβ”€β”€ tf_weights.h5          # Original TensorFlow/Keras HDF5 model weights
└── onnx/                  # Optimized ONNX model files for inference
    └── astra-clr.onnx     
  • tf_weights.h5: The raw model weights exported from the TensorFlow-based ASTRA training pipeline. These weights are ideal for resuming pre-training or performing fine-tuning.
  • onnx/astra-clr.onnx: A serialized, platform-independent execution format optimized for production. This file is designed to be consumed directly by the astra_infer package.

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Dataset used to train ashrot/astra-clr-base