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Legal NLP Releases E5 and BGE Sentence Embedding models and two subpoena demo apps

John Snow Labs

of the library comes with optimized sentence embedding models for RAG applications in the Legal domain and new demo apps for Subpoenas. New demo apps for Subpoena analysis A subpoena is a formal document issued by a court, grand jury, legislative body or committee, or authorized administrative agency. Version 1.20.0 Fancy trying?

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Finance NLP releases QA-based on Financial Alpaca and FIQA datasets, new LLM demos, new Financial Sentiment Models and Visual NER.

John Snow Labs

New Financial Alpaca-based QA model We have used the Financial Alpaca dataset to train a Flan-T5 models for specific financial question-answering without a given context. FIQA-based QA model Similarly, we used the FIQA dataset to train another Flan-T5 model, also for financial question-answering. Demo available here.

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Legal NLP Releases Law Stack Exchange Classifier, Subpoena NER and more

John Snow Labs

Law Stack Exchange Classifier This new model is a text classifier trained on the Law Stack Exchange dataset. Subpoena NER This model is trained on an in-house dataset to identify entities in Subpoena documents. We’ve got 30-days free licenses for you with technical support from our legal team of technical and SME.

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Bringing fresh capabilities for Legal research and applications with Legal NLP

John Snow Labs

To support the utilization, training, and fine-tuning of models for the legal domain, Legal NLP is introducing new models: word embedding models, which generate vector representations of words (or tokens), and sentence embedding models, which create vector representations for longer pieces of text such as sentences, paragraphs, and documents.

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Better embeddings and better models in Finance NLP

John Snow Labs

To provide the capabilities to use, train, and finetune models for Finance, Finance NLP is releasing two categories of embedding models: word embedding models that create vector representations of words (or tokens), and sentence embedding models that create vector representations of longer chunks of text (e.g., NER, Relation Extraction).

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Why Kintana Isn’t a Long-Term Viability for Enterprises

Flexagon

It also suffers from limited technical support. The process requires buying new licenses, migrating data, and training employees to use the new edition. Unfortunately, Kintana doesn’t have much in the way of support and community—the many changes of ownership have interfered with customer assistance.

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Finance NLP Releases new E5 Sentence Embedding model and Aspect-based Sentiment Analysis

John Snow Labs

Sentence Embedding Model The new sentence embedding model expands the capabilities of the library for Retrieval Augmented Generation (RAG) applications and the capability to train text classification models. Text embeddings by weakly-supervised contrastive pre-training.” Don’t forget to check our notebooks and demos.