Search Results for "entity" - Page 4
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Showing 82 open source projects for "entity"
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An Vietnamese Information Extractor
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TBLTools is a set of GATE processing resources that implements the Fast Transformation Based Learning Algorithm. You can train it to learn rules for NLP tasks such as Named Entity Recognition and Shallow parsing.
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T-Rex (Trainable Relation Extraction) is a highly configurable machine learning-based Information Extraction from Text framework, which includes tools for document classification, entity extraction and relation extraction.
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Zeeble Bug is a basic A-life program designed for lava-lamp style desktop viewing of a pond filled with "bugs". It employs a simple neural networks, genes, and varied water conditions to keep the pond a shifting and evolving entity.
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Ship Agents FasterGemini Enterprise Agent Platform lets you rapidly build, scale, govern and optimize production-ready agents grounded in your organization's data. The platform enables developers to build custom or pre-built agents for virtually any use case. New customers get $300 in free credits.
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Gamel (pronounced like camel) is a library written in C++ for use in games. Gamel includes common search and sort algorithms, easy-to-use networking methods, logging, 2D/3D distance calculation, entity classes for RPG and FPS games, pathfinding and more.
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layoutlm-base-uncased
Multimodal Transformer for document image understanding and layout
...It achieves state-of-the-art results in form understanding and information extraction benchmarks. This model is particularly useful for document AI applications like document classification, question answering, and named entity recognition. -
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Bio_ClinicalBERT
ClinicalBERT model trained on MIMIC notes for clinical NLP tasks
...It was initialized from BioBERT-Base v1.0 and further pre-trained on all clinical notes from the MIMIC-III database (~880M words), which includes ICU patient records. The training focused on improving performance in tasks like named entity recognition and natural language inference within the healthcare domain. Notes were processed using rule-based sectioning and tokenized with SciSpacy. Training was done for 150,000 steps using a batch size of 32, max sequence length of 128, and a masked language modeling objective with a 0.15 mask probability. Bio_ClinicalBERT is available through Hugging Face's Transformers library for easy integration. ...
