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@raphaelsty raphaelsty released this 26 Nov 10:42
· 6 commits to main since this release
1.1.3
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PyLate Update

This release introduces several new features and improvements:

1. Native Stanford-NLP Model Support

PyLate now supports loading Stanford-NLP models directly, without requiring manual weight conversion. This includes models like Jina-ColBERTv2 and local models. Use the model name when creating a PyLate model.

2. FastAPI Integration

PyLate now allows serving embeddings via a FastAPI server. The server supports dynamic batch processing to handle multiple requests efficiently. See the documentation for details.

3. DictDataset Added

DictDataset has been introduced for handling datasets more effectively during training and inference.

4. Model Card Generation

Trained models now include a generated Model Card containing metadata about the model and training setup.

Fixes and Enhancements

  • Fixed an issue where dataset processing during training could become unresponsive.
  • Improved performance and reliability for training and inference.
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