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Document Level Sentiment Analysis is an End-to-End deep learning workflow using Hugging Face transformers API to do a "classification" task at document level, to analyze the sentiment of input document containing English sentences or paragraphs.

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PROJECT NOT UNDER ACTIVE MANAGEMENT

This project will no longer be maintained by Intel.
Intel will not provide or guarantee development of or support for this project, including but not limited to, maintenance, bug fixes, new releases or updates.
Patches to this project are no longer accepted by Intel.
If you have an ongoing need to use this project, are interested in independently developing it, or would like to maintain patches for the community, please create your own fork of the project.

E2E DLSA

DLSA is Intel optimized representative End-to-end Fine-Tuning & Inference pipeline for Document level sentiment analysis using BERT model implemented with Hugging face transformer API. the code supports single node and multinode implementations.

DLSA Workflow

Please see the GitHub page for the details. https://intel.github.io/document-level-sentiment-analysis/

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Document Level Sentiment Analysis is an End-to-End deep learning workflow using Hugging Face transformers API to do a "classification" task at document level, to analyze the sentiment of input document containing English sentences or paragraphs.

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