Repository History
26 repositories tagged with NLP
Trafilatura: Advanced Web Scraping and Text Extraction in Python
Trafilatura is a robust Python package and command-line tool designed for gathering text and metadata from the web. It simplifies web crawling, scraping, and content extraction, transforming raw HTML into structured data. Widely adopted by major companies and institutions, it offers high efficiency and accuracy for various text processing needs.
judges: A Python Library for LLM-as-a-Judge Evaluators
The `judges` library from Databricks provides a concise and powerful way to use and create LLM-as-a-Judge evaluators. It offers a curated set of pre-built judges for various use cases, backed by research, and supports both off-the-shelf usage and custom judge creation. This tool helps developers effectively evaluate the performance and quality of their Large Language Models.
Jieba: The Leading Python Library for Chinese Text Segmentation
Jieba is a highly popular and efficient Python library designed for Chinese text segmentation. It offers various cutting modes, including accurate, full, and search engine modes, making it versatile for different NLP tasks. With features like custom dictionaries and part-of-speech tagging, Jieba provides a comprehensive solution for processing Chinese text.
LLMBox: A Comprehensive Python Library for LLM Training and Evaluation
LLMBox is a comprehensive Python library designed for implementing Large Language Models, offering a unified training pipeline and extensive model evaluation capabilities. It provides a one-stop solution for both training and utilizing LLMs, emphasizing flexibility and efficiency. Developers can leverage its diverse training strategies and blazingly fast inference for their LLM projects.
NUDGE: Lightweight Non-Parametric Embedding Fine-Tuning for Retrieval
NUDGE is a lightweight, non-parametric tool designed to fine-tune pre-trained embeddings, significantly enhancing retrieval and RAG pipelines. It operates by adjusting data embeddings directly, rather than modifying model parameters, to maximize accuracy. This approach often leads to over 10% improvement in retrieval accuracy and runs in minutes.
LLMSanitize: An Open-Source Library for Contamination Detection in NLP and LLM Datasets
LLMSanitize is an open-source Python library designed for detecting contamination in NLP datasets and Large Language Models (LLMs). It offers a comprehensive suite of methods, ranging from string matching to model likelihood and embedding similarity, to ensure data integrity. This tool is crucial for researchers and developers working with LLMs to maintain the reliability of their models and evaluations.
LLM Reasoners: Advanced Library for Large Language Model Reasoning
LLM Reasoners is a powerful Python library designed to significantly enhance the complex reasoning capabilities of Large Language Models. It offers a comprehensive suite of cutting-edge search algorithms, intuitive visualization tools, and optimized performance for efficient LLM inference. The library prioritizes rigorous implementation and reproducibility, making it a reliable tool for researchers and developers in the AI field.
TextMachina: A Python Framework for MGT Dataset Generation
TextMachina is a modular and extensible Python framework designed for creating high-quality, unbiased datasets for Machine-Generated Text (MGT) tasks. It supports detection, attribution, and boundary detection, offering a user-friendly pipeline with LLM integrations, prompt templating, and bias mitigation. This tool streamlines the process of building robust models for understanding and identifying AI-generated content.
sumy: Automatic Text Summarization for Documents and HTML Pages
sumy is a robust Python module designed for automatic summarization of text documents and HTML pages. It provides various summarization methods, supports multiple natural languages, and offers both a command-line utility and a flexible Python API. This versatile tool enables users to efficiently extract concise summaries from lengthy content.
Toolkit-for-Prompt-Compression: A Unified Toolkit for LLM Prompt Compression
PCToolkit is a unified, plug-and-play toolkit designed for efficient prompt compression in Large Language Models (LLMs). It provides state-of-the-art compression methods, diverse datasets, and comprehensive metrics for evaluating performance. This modular toolkit simplifies the process of condensing input prompts while preserving crucial information.
Judgy: Correcting LLM Judge Bias for Reliable AI Model Evaluation
Judgy is a Python package designed to improve the reliability of evaluations performed by LLM-as-Judges. It provides tools to estimate the true success rate of a system by correcting for LLM judge bias and generating confidence intervals through bootstrapping. This helps ensure more accurate and trustworthy assessments of AI model performance.
txtinstruct: Building Instruction-Tuned Models with Custom Data
txtinstruct is a Python framework designed for training instruction-tuned models. It focuses on supporting open data and models, enabling users to build their own instruction-following datasets and train models without licensing ambiguity. This project simplifies the process of creating custom instruction-tuned solutions.