Large Language Models
Showing 36 of 44 projects
A platform to run, manage, and serve open-source large language models (LLMs) locally or on your own infrastructure.
A platform to run, manage, and serve open-source large language models locally with a simple CLI and REST API.
A comprehensive open-source guide covering prompt engineering techniques, papers, notebooks, and resources for LLMs, RAG, and AI agents.
Run large language models (LLMs) privately on everyday desktops and laptops without requiring API calls or GPUs.
A web UI and optimization library for running and fine-tuning open-source AI models locally with 2x faster training and 70% less VRAM.
A cross-platform desktop client for ChatGPT, Claude, and other LLMs with local data storage and a powerful prompt library.
A unified deep learning system for efficient large-scale model training and inference with advanced parallelism strategies.
An open platform for training, serving, and evaluating large language model based chatbots.
🪢 Open source AI engineering platform: LLM evals, observability, metrics, prompt management, playground, datasets. Integrates with OpenTelemetry, LangChain, OpenAI SDK, LiteLLM, and more. 🍊YC W23
Open-source AI orchestration framework for building context-engineered, production-ready LLM applications in Python.
An open-source framework for financial large language models, enabling cost-effective fine-tuning for tasks like sentiment analysis and forecasting.
A low-level tensor library for machine learning with integer quantization, automatic differentiation, and zero runtime allocations.
A curated list of open-source large language models licensed for commercial use, including models for general text and code generation.
A curated list of modern Generative AI projects, services, models, and resources across text, image, video, audio, and coding.
Deep Lake is a multimodal data lake and vector store optimized for AI, enabling scalable data management, retrieval, and training for LLM and deep learning applications.
A collection of libraries to optimize AI model performance through inference, infrastructure, and fine-tuning techniques.
A collection of libraries to optimize AI model performance through inference acceleration, infrastructure efficiency, and fine-tuning optimization.
An open-source AI agent platform for financial analysis, automating equity research, algorithmic trading, and risk assessment using LLMs.
A curated list of awesome resources for applying LLMs and deep learning to financial market analysis and algorithmic trading.
An open-source pipeline for training medical domain GPT models using PT, SFT, RLHF, DPO, ORPO, and GRPO methods.
A curated collection of resources for building, training, serving, and optimizing production-grade Large Language Model applications.
An open-source, locally-runnable code completion engine using large language models that works on CPU.
Seamlessly integrate large language models like ChatGPT into scikit-learn for enhanced text analysis tasks.
An open-source framework for building multimodal AI systems that enable large language models to understand and chat about videos and images.
A JAX/Flax-based framework for easy and scalable pre-training, fine-tuning, evaluation, and serving of large language models.
A git prepare-commit-msg hook that automatically generates commit messages using OpenAI language models.
A high-performance, scalable LLM library and reference implementation written in pure Python/JAX for training on TPUs and GPUs.
An experimental toolkit that automatically generates and maintains codebase documentation using LLMs like GPT-4.
A neuro-symbolic Python framework that combines classical programming with LLMs through composable primitives and design-by-contract validation.
A comprehensive PHP generative AI framework for building applications with OpenAI, Anthropic, Mistral, and other LLMs.
An open-source suite featuring financial large language models (FinMA), instruction datasets (FIT), and evaluation benchmarks (FinBen) for financial AI.
A JAX-based framework for training large language models with a focus on legibility, scalability, and reproducibility.
A Python library for generating high-quality synthetic tabular data using GANs, diffusion models, and large language models.
A JAX-based machine learning framework for configuring and training large-scale models with high efficiency on TPUs and GPUs.
A Neovim plugin for interacting with various large language models (LLMs) like ChatGPT, Copilot, and local models directly within the editor.
A tool-augmented LLM that uses NCBI Web APIs to answer biomedical questions with high accuracy and reduced hallucinations.
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