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Open-source project that supports deploying, serving, monitoring, or operating AI and machine-learning systems.
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Lifelines is a complete survival analysis library, written in pure Python.
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Lightly is a computer vision framework for self-supervised learning.
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A graph sampling extension library for NetworkX with a Scikit-Learn like API.
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A header-only C++11 Neural Network library. Low dependency, native traditional chinese document.
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The llama-cpp-agent framework is a tool designed for easy interaction with Large Language Models.
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Provides a central interface to connect your LLM's with external data.
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LlamaIndex is a data framework for your LLM applications.
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Build agents which are controlled by LLMs.
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LLM App is a Python library that helps you build real-time AI-powered data pipelines with few lines of code.
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Extensible Toolkit for Finetuning and Inference of Large Foundation Models.
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A deep research tool for searching academic sources, the web, and private documents with local or cloud LLMs. opensource.
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Inspired on Private GPT with the GPT4ALL model replaced with the Vicuna-7B model and using the InstructorEmbeddings instead of LlamaEmbeddings.
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Godot 4.x asset that enables NPCs to interact with players using local LLMs for structured, offline-first learning conversations in games.
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A tool that provides a Model Context Protocol (MCP) server for any web application with an OpenAPI specification.
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Using Low-rank adaptation to quickly fine-tune diffusion models.
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Tensorflow and OpenAI Clarity's Lucid adapted for PyTorch.
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A low-code framework for building custom AI models like LLMs and other deep neural networks. opensource.
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TypeScript SDK to easily call 100+ LLMs using OpenAI's format.
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Chinese LLM, Based on LLaMA and fine tune by Stanford Alpaca, Alpaca LoRA, Japanese-Alpaca-LoRA.
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Open-source project that catalogs AI services and resources for browsing by feature or use case.
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Markov chain Monte Carlo (MCMC) for Bayesian analysis in Julia.
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A chat LLM based on the state-space model architecture.
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A Julia package for manifold learning and nonlinear dimensionality reduction.