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Accelerating scope 3 emissions accounting: LLMs to the rescue

IBM Journey to AI blog

Figure 1: Framework for estimating Scope3 emissions using large language models We conducted extensive experiments involving several cutting-edge LLMs including roberta-base, bert-base-uncased, and distilroberta-base-climate-f. Additionally, we explored non-foundation classical models based on TF-IDF and Word2Vec vectorization approaches.

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Accelerate hyperparameter grid search for sentiment analysis with BERT models using Weights & Biases, Amazon EKS, and TorchElastic

AWS Machine Learning Blog

Transformer-based language models such as BERT ( Bidirectional Transformers for Language Understanding ) have the ability to capture words or sentences within a bigger context of data, and allow for the classification of the news sentiment given the current state of the world. The code can be found on the GitHub repo.

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