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AI orchestration framework to build customizable, production-ready LLM applications. Connect components (models, vector DBs, file converters) to pipelines or agents that can interact with your data. With advanced retrieval methods, it's best suited for building RAG, question answering, semantic search or conversational agent chatbots.
Module for automatic summarization of text documents and HTML pages.
AdalFlow: The library to build & auto-optimize LLM applications.
A modular RL library to fine-tune language models to human preferences
Python implementation of TextRank algorithms ("textgraphs") for phrase extraction
Gathers machine learning and Tensorflow deep learning models for NLP problems, 1.13 < Tensorflow < 2.0
Efficient Retrieval Augmentation and Generation Framework
Transformers 库快速入门教程
Returns latest research results by crawling arxiv papers and summarizing abstracts. Helps you stay afloat with so many new papers everyday.
TextRank implementation for Python 3.
Summarization Papers
pytorch implementation of "Get To The Point: Summarization with Pointer-Generator Networks"
Toolkit for fine-tuning, ablating and unit-testing open-source LLMs.
Converse with book - Built with GPT-3
Basic statistics for Julia
LLM for Long Text Summary (Comprehensive Bulleted Notes)
Automatically generate headlines to short articles
AWS Generative AI CDK Constructs are sample implementations of AWS CDK for common generative AI patterns.
Models to perform neural summarization (extractive and abstractive) using machine learning transformers and a tool to convert abstractive summarization datasets to the extractive task.