Search Results for "text summarization"

Claude Cookbooks is a curated collection of practical examples, notebooks, and implementation guides that demonstrate how to effectively use Claude’s API across a wide range of tasks. It serves as both a learning resource and a reference library, helping developers understand how to apply AI capabilities such as classification, summarization, and retrieval-augmented generation in real-world scenarios. The repository includes structured examples for integrating Claude with external tools, databases, and APIs, showcasing how to extend its functionality beyond basic text generation. It also covers advanced techniques like sub-agent orchestration, prompt optimization, and automated evaluation workflows. ...

The openai-php/client library is a PHP client for interacting with OpenAI’s API, enabling developers to integrate OpenAI models into their PHP applications. It simplifies sending API requests to access language models, generating text, processing natural language, and utilizing OpenAI’s advanced features. The library is designed to be easy to use, allowing developers to quickly set up and use OpenAI’s capabilities within their PHP projects.

...Innovation is happening at a rapid pace, models can understand concepts in documents, audio, images and more. Machine-learning pipelines to run extractive question-answering, zero-shot labeling, transcription, translation, summarization and text extraction. Cloud-native architecture that scales out with container orchestration systems (e.g. Kubernetes). Applications range from similarity search to complex NLP-driven data extractions to generate structured databases. The following applications are powered by txtai.

Fairseq(-py) is a sequence modeling toolkit that allows researchers and developers to train custom models for translation, summarization, language modeling and other text generation tasks. We provide reference implementations of various sequence modeling papers. Recent work by Microsoft and Google has shown that data parallel training can be made significantly more efficient by sharding the model parameters and optimizer state across data parallel workers. These ideas are encapsulated in the new FullyShardedDataParallel (FSDP) wrapper provided by fairscale. ...

...Provide a variety of neural network components and recurrence models (covering tasks such as Chinese word segmentation, named entity recognition, syntactic analysis, text classification, text matching, metaphor resolution, summarization, etc.). Trainer provides a variety of built-in Callback functions to facilitate experiment recording, exception capture, etc. Automatic download of some datasets and pre-trained models.

nlp_chinese_corpus is a large-scale Chinese corpus collection for natural language processing research and development. It was created to make high-volume Chinese text data easier to access for students, researchers, and practitioners. The repository gathers several major datasets, including Chinese Wikipedia entries, news articles, encyclopedia-style question answering data, community question answering data, and Chinese-English translation sentence pairs. Each dataset includes...

textteaser is an automatic text summarization algorithm implemented in Python. It extracts the most important sentences from an article to generate concise summaries that retain the core meaning of the original text. The algorithm uses features such as sentence length, keyword frequency, and position within the document to determine which sentences are most relevant.

The JINSECT toolkit is a Java-based toolkit and library that supports and demonstrates the use of n-gram graphs within Natural Language Processing applications, ranging from summarization and summary evaluation to text classification and indexing.