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Introduction of Logistic Regression Classifier: Added a new classification kernel leveraging Logistic Regression for efficient text categorization without the need for fine-tuning.
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Support for Multiple Pooling Strategies: Implemented various pooling strategies, including
MEAN,MEAN_MASKED,MAX,MAX_MASKED,CLS,SUM, andATTENTION_WEIGHTEDfor flexible embedding generation. -
Template and Instruct Models: Introduced support for instruct templates with models like
intfloat/multilingual-e5-large-instructto enhance performance by utilizing structured templates. -
Model Export and HuggingFace Integration: Simplified the process of saving and publishing models to HuggingFace with automatic model cards and additional metadata such as tags and languages.
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Inference Server: Added a dockerized inference server with an HTTP API to facilitate deployment. This includes new scripts for starting the server both in a docker container and on a host machine.
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Improved Documentation: Updated and expanded documentation, including examples for training models, classification kernels, pooling strategies, model export, and inference.