Search Results for "text summarization java code" - Page 2
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Showing 34 open source projects for "text summarization java code"
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DBpedia Spotlight is a tool for annotating mentions of DBpedia resources in natural language text. The source code is now hosted on GitHub: https://github.com/dbpedia-spotlight
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This project aims to implement in java the following text mining techniques: Text Language Detection, Keywords and keyphrases extraction, Text Classification, Text Clustering, Single or multiple documents Summarization, Plagiarism Detection.
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This is a Java-based project for complex event extraction from text and co-reference resolution. Currently the code can read BioNLP shared task format (http://2011.bionlp-st.org/) and i2b2 Natural Language Processing for Clinical Data shared task format (https://www.i2b2.org/NLP/DataSets/Main.php). Event extraction includes finding events and the parameters for an event in a text. The method is based on SVM but other ML algorithms can be adopted. The method details are explained...
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Performs summarization, categorization, key phrase generation,full text indexing and search,part of speech tagging,identification of place and human names in various document format. Latest code is available at http://www.twit88.com/
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Picsart Enterprise Background Removal API for Stunning eCommerce VisualsWith our Remove Background API tool, you can access the transformative capabilities of automation , which will allow you to turn any photo asset into compelling product imagery. With elevated visuals quality on your digital platforms, you can captivate your audience, and therefore achieve higher engagement and sales.
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BLEURT-20-D12
Custom BLEURT model for evaluating text similarity using PyTorch
BLEURT-20-D12 is a PyTorch implementation of BLEURT, a model designed to assess the semantic similarity between two text sequences. It serves as an automatic evaluation metric for natural language generation tasks like summarization and translation. The model predicts a score indicating how similar a candidate sentence is to a reference sentence, with higher scores indicating greater semantic overlap. Unlike standard BLEURT models from TensorFlow, this version is built from a custom PyTorch... -
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gemma-7b
Compact, state-of-the-art LLM by Google for text generation tasks
Gemma-7B is a lightweight, open-source, decoder-only language model developed by Google, built using the same research and technology behind the Gemini family. With 8.5 billion parameters and an 8192-token context window, it is optimized for English text generation tasks like question answering, summarization, reasoning, and creative writing. Trained on 6 trillion tokens including web documents, code, and mathematical texts, Gemma-7B provides competitive performance across a wide range of NLP... -
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Llama-3.2-1B-Instruct
Instruction-tuned 1.2B LLM for multilingual text generation by Meta
Llama-3.2-1B-Instruct is Meta’s multilingual, instruction-tuned large language model with 1.24 billion parameters, optimized for dialogue, summarization, and retrieval tasks. It builds upon the Llama 3.1 architecture and incorporates fine-tuning techniques like SFT, DPO, and quantization-aware training for improved alignment, efficiency, and safety. The model supports eight primary languages (including English, Spanish, Hindi, and Thai) and was trained on a curated mix of publicly available... -
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Llama-2-7b-hf
Llama-2-7B is a 7B-parameter transformer model for text generation
Llama-2-7B is a foundational large language model developed by Meta as part of the Llama 2 family, designed for general-purpose text generation tasks. It is a 7 billion parameter auto-regressive transformer trained on 2 trillion tokens from publicly available sources, using an optimized architecture without Grouped-Query Attention (GQA). This model is the pretrained version, intended for research and commercial use in English, and can be adapted for downstream applications such as summarization... -
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Llama-2-7b
7B-parameter foundational LLM by Meta for text generation tasks
... processing tasks, such as summarization, completion, and code generation. It demonstrates solid performance on academic benchmarks like MMLU and TruthfulQA, improving on its predecessor, Llama 1. The Llama-2-7B model is released under Meta’s Llama 2 Community License, which allows for commercial use under certain conditions, especially for companies with fewer than 700 million MAUs. -
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