Transformers-compatible library for applying various compression algorithms to LLMs for optimized deployment with vLLM

Lightweight wrapper for cortecs.ai enabling 🔵 instant provisioning

PRAW, an acronym for "Python Reddit API Wrapper", is a python package that allows for simple access to Reddit's API.

The code used to train and run inference with the ColPali architecture.

🦾 Take control of your AI agents

Module, Model, and Tensor Serialization/Deserialization

Use PEFT or Full-parameter to finetune 450+ LLMs (Qwen2.5, InternLM3, GLM4, Llama3.3, Mistral, Yi1.5, Baichuan2, DeepSeek-R1, ...) and 150+ MLLMs (Qwen2.5-VL, Qwen2-Audio, Llama3.2-Vision, Llava, I…

Distilabel is a framework for synthetic data and AI feedback for engineers who need fast, reliable and scalable pipelines based on verified research papers.

Retrieval and Retrieval-augmented LLMs

syntax highlighting component for react with prismjs or highlightjs ast using inline styles

Supabase for Machine Learning

🌐 Internationalization (i18n) for Next.js

A high-throughput and memory-efficient inference and serving engine for LLMs

🧊 Glasskube Apps Operator

Promptimize is a prompt engineering evaluation and testing toolkit.

The universal tool suite for vector database management. Manage Pinecone, Chroma, Qdrant, Weaviate and more vector databases with ease.

🔍 LangKit: An open-source toolkit for monitoring Large Language Models (LLMs). 📚 Extracts signals from prompts & responses, ensuring safety & security. 🛡️ Features include text quality, relevance m…

Open source libraries and APIs to build custom preprocessing pipelines for labeling, training, or production machine learning pipelines.

A framework for few-shot evaluation of language models.

Adding guardrails to large language models.

QLoRA: Efficient Finetuning of Quantized LLMs

🗃 Open source self-hosted web archiving. Takes URLs/browser history/bookmarks/Pocket/Pinboard/etc., saves HTML, JS, PDFs, media, and more...

State-of-the-Art Text Embeddings

A collection of public TagPacks

Portfolio analytics for quants, written in Python

Combining tree-boosting with Gaussian process and mixed effects models

BackTest and Run CryptoCurrency Trading Strategies

Time series forecasting with PyTorch