Streamline Model Inference Pipeline and Checkpoint Management #26
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- Removed gdown dependency for downloading model checkpoints and replaced it with a custom download function in model.py. - Introduced a new method to retrieve model checkpoints with error handling for invalid names and custom paths. - Updated README to include details about the new live inference script for pretrained models. - Added a new task in pyproject.toml for running the pretrained model inference script. - Cleaned up the predictor class by delegating checkpoint validation to the model module.
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This PR introduces comprehensive improvements to our model inference and checkpoint management system:
Key Changes:
Documentation Updates:
New Tasks:
live-inference-pretrainedtask for quick model testingThis PR simplifies the user experience for model inference while improving code maintainability and reducing dependency overhead.