Search Results for "summarization" - Page 6
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Showing 143 open source projects for "summarization"
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most-exploratory-search
Exploratory search with entailment and summarization
The BGU NLP project: http://www.cs.bgu.ac.il/~nlpproj/ -
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Graph-based Extraction and Summarization - a generic graph-based summarization framework. Basic functionality is provided - third-party modules can be plugged in.
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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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SIDoBI is an automatic summarization system for documents in Indonesian language. It is an acronym for Sistem Ikhtisar Dokumen untuk Bahasa Indonesia. SIDoBI is built based on MEAD, a public domain portable multi-document summarization system.
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Document summarization system. By adding document content to system, user queries will generate a summary document containing the available information to the system.
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GoldenOrb is a java library under the Apache License V2.0 for correlation, summarization and clustering of text information.
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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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WebCQ is a continual query system for large-scale Web information monitoring. It tracks various changes to static and dynamic web pages, delivers personalized notifications and summarization with prioritization, and analyzes page structures.
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Text classification and summarization library for .NET. A port of the Classifier4J Java library (see http://classifier4j.sourceforge.net).
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Nemotron 3
Large language model developed and released by NVIDIA
...This configuration supports a massive context length of up to 1 million tokens, making it suitable for long-context reasoning, agentic tasks, extended dialogues, and applications like code generation or document summarization. -
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bart-large-cnn
Summarization model fine-tuned on CNN/DailyMail articles
...The model supports usage in PyTorch, TensorFlow, and JAX, and is integrated with the Hugging Face pipeline API for simple deployment. Due to its size and performance, it's widely used in real-world summarization applications such as news aggregation, legal document condensing, and content creation. -
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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 transformer library. It requires installing the model-specific library from GitHub to function properly. ... -
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Gemopus
Stable fine-tuned Gemma model for structured, clear responses
...It also strengthens technical explanations, balancing rigor with accessibility. While not intended as a production-ready system, it serves as a high-quality local assistant for structured writing, summarization, and coding tasks. Limitations include potential hallucinations in complex domains and weaker performance compared to larger frontier models. -
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t5-base
Flexible text-to-text transformer model for multilingual NLP tasks
t5-base is a pre-trained transformer model from Google’s T5 (Text-To-Text Transfer Transformer) family that reframes all NLP tasks into a unified text-to-text format. With 220 million parameters, it can handle a wide range of tasks, including translation, summarization, question answering, and classification. Unlike traditional models like BERT, which output class labels or spans, T5 always generates text outputs. It was trained on the C4 dataset, along with a variety of supervised NLP benchmarks, using both unsupervised denoising and supervised objectives. The model supports multiple languages, including English, French, Romanian, and German. ... -
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t5-small
T5-Small: Lightweight text-to-text transformer for NLP tasks
T5-Small is a lightweight variant of the Text-To-Text Transfer Transformer (T5), designed to handle a wide range of NLP tasks using a unified text-to-text approach. Developed by researchers at Google, this model reframes all tasks—such as translation, summarization, classification, and question answering—into the format of input and output as plain text strings. With only 60 million parameters, T5-Small is compact and suitable for fast inference or deployment in constrained environments. It was pretrained on the C4 dataset using both unsupervised denoising and supervised learning on tasks like sentiment analysis, NLI, and QA. ... -
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Llama-3.2-1B-Instruct
Instruction-tuned 1.2B LLM for multilingual text generation by Meta
...Llama-3.2-1B is lightweight enough for deployment on constrained devices like smartphones, using formats like SpinQuant and QLoRA to reduce model size and latency. Despite its small size, it performs competitively across benchmarks such as MMLU, ARC, and TLDR summarization. The model is distributed under the Llama 3.2 Community License, requiring attribution and adherence to Meta’s Acceptable Use Policy. -
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Llama-3.2-1B
Llama 3.2–1B: Multilingual, instruction-tuned model for mobile AI
meta-llama/Llama-3.2-1B is a lightweight, instruction-tuned generative language model developed by Meta, optimized for multilingual dialogue, summarization, and retrieval tasks. With 1.23 billion parameters, it offers strong performance in constrained environments like mobile devices, without sacrificing versatility or multilingual support. It is part of the Llama 3.2 family, trained on up to 9 trillion tokens and aligned using supervised fine-tuning, preference optimization, and safety tuning. ... -
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VaultGemma
VaultGemma: 1B DP-trained Gemma variant for private NLP tasks
VaultGemma is a sub-1B parameter variant of Google’s Gemma family that is pre-trained from scratch with Differential Privacy (DP), providing mathematically backed guarantees that its outputs do not reveal information about any single training example. Using DP-SGD with a privacy budget across a large English-language corpus (web documents, code, mathematics), it prioritizes privacy over raw utility. The model follows a Gemma-2–style architecture, outputs text from up to 1,024 input tokens,...
