Sparknlp 1189 Introducing Phi4 #14606
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- Introduced `Phi4` class for the state-of-the-art Phi-4 model by Microsoft Research, including methods for encoding, decoding, and tagging. - Added `Phi4Transformer` for integration with Spark NLP, enabling pretrained model loading and configuration. - Implemented `Phi4Tokenizer` for byte pair encoding specific to the Phi-4 model. - Updated `BpeTokenizer` to support the new Phi-4 tokenizer. - Added tests for `Phi4Transformer` to ensure functionality and performance. - Updated resource downloader to include `Phi4Transformer` for pretrained model access.
- Expanded the model description to include detailed information on parameters, intended use, benchmarks, safety, limitations, and usage instructions. - Improved formatting for better readability and clarity. - Added references for further information on the Phi-4 model.
- Introduced `Phi4Transformer` class for the state-of-the-art Phi-4 model by Microsoft Research, enabling advanced reasoning and NLP tasks. - Added support for loading pretrained models and configuration parameters. - Implemented a loader for the Phi-4 model in the internal module. - Created unit tests to validate the functionality of the `Phi4Transformer`. - Updated the main `__init__.py` to include the new transformer in the module exports.
- Created a detailed markdown file for the `Phi4Transformer`, outlining its features, usage, and pretrained model loading instructions. - Added a Jupyter notebook demonstrating the integration of the Phi-4 model with Spark NLP and Intel OpenVINO, including installation steps and example code. - Enhanced the Scala implementation comments for better clarity and formatting. - Updated the test specifications to reflect changes in the handling of temperature settings during predictions.
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Description
This PR introduces Phi4 model into SparkNLP
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