Open-source alternatives to Llama Chinese

This project is a quantized fine-tuning framework for large language models. It implements a low-rank adaptation library and a four-bit quantizer to reduce the GPU memory requirements needed to train large models. The framework utilizes four-bit quantization and low-rank adapters to enable model training on consumer-grade hardware. It further reduces the memory footprint through double quantization and a paged optimizer that offloads states to system RAM. The system supports distributed training across multiple GPUs to handle larger parameter scales and includes utilities for custom dataset

Welcome to the Node on FHIR Cookbook. This repository contains cookbook recipes for writing Node/Javascript software that's intended to be used in clinical, laboratory, and healthcare settings. If you're using Node.js (and the Meteor build pipeline) and need to implement a HIPAA audit log, or do…

JavaScript and Node.js cheatsheets

“悟道”项目现有7个开源模型成果，本仓库提供所有开源成果的模型参数文件链接。

OpenLLM is a framework for deploying, managing, and scaling open-source large language models

KoAlpaca: 한국어 명령어를 이해하는 오픈소스 언어모델 (KoAlpaca: An open-source language model to understand Korean instructions)

LiteLLM is a unified gateway and proxy server designed to centralize access to over one hundred language model providers. It provides a standardized API interface that abstracts vendor-specific schemas, allowing developers to interact with diverse models through a single, consistent format. By acting as a central traffic management layer, it enables organizations to route, secure, and govern model interactions across multiple deployments. The platform distinguishes itself through its policy-driven architecture, which uses configuration-based routing to manage traffic distribution, load balanc

StarCoder2 is a family of code generation models (3B, 7B, and 15B), trained on 600+ programming languages from The Stack v2 and some natural language text such as Wikipedia, Arxiv, and GitHub issues. The models use Grouped Query Attention, a context window of 16,384 tokens, with sliding window…

Petals is a decentralized framework and inference engine for running large language models across a peer-to-peer network. It enables the execution of models that exceed the memory of any single machine by splitting computations and model layers across a collaborative swarm of GPUs. The system functions as a collaborative compute network where participants share local GPU resources and host model weights. It supports distributed prompt-tuning to adapt massive models to specific tasks and allows for the establishment of private compute swarms to process sensitive data within restricted, trusted

The best short-form writing about Rust, collected.

MultimodalC4 is a multimodal extension of c4 that interleaves millions of images with text.

Please refer to our new GitHub Wiki which documents our efforts in detail in creating the open source version of GitHub Copilot

Deepeval is a framework for testing and evaluating large language model applications. It provides a suite of tools for executing automated regression tests, validating model output quality against defined standards, and tracing the execution of complex agent workflows. By integrating these capabilities into development pipelines, the platform ensures consistent performance and reliability throughout the software lifecycle. The platform distinguishes itself through its focus on programmatic validation and observability. It utilizes secondary language models to score output quality and employs

ChatBot Injection and Exploit Examples: A Curated List of Prompt Engineer Commands - ChatGPT

GoBooks is a curated directory and index of technical literature designed to support software engineering development and professional growth. The project functions as a structured repository that organizes educational materials into learning paths, allowing developers to discover resources tailored to their specific proficiency levels and career goals. The collection is centered on the Go programming language, providing a progression of books and guides that range from fundamental syntax to advanced system design patterns. By utilizing a structured classification system, the repository enabl

Dolly is an instruction-tuned large language model designed to follow complex natural language directions. It operates as a causal language model that predicts the next token in a sequence to generate coherent conversational responses and perform tasks such as brainstorming, classification, and question answering. The project focuses on the development of models using open datasets suitable for commercial application. It enables the creation of instruction-following models by utilizing curated collections of human-generated instruction-response pairs. The repository provides capabilities for

IF is a text-to-image diffusion system that translates natural language descriptions into visual imagery. The project provides a generative pipeline for creating images, an inpainting tool for modifying specific image sections, and a super-resolution upscaler to increase pixel density and clarity. The system includes a concept fine-tuning framework that allows for the teaching of new visual concepts by updating a small set of parameters. It also supports image style transfer to apply the aesthetic characteristics of a reference image to a new output.

DeepSeek-V3 is a large language model that provides comprehensive resources for model utilization, including technical specifications, pre-trained weights, and evaluation benchmarks. The project details the core transformer architecture, including parameter counts and multi-token prediction modules, while supporting native 8-bit floating-point quantization. The repository offers extensive support for local and distributed inference through integration with multiple frameworks and engines. It includes documentation for deploying the model across various hardware configurations, such as GPUs an

That's because you are a amazing! Here's how it works:

This project is an educational resource and technical reference archive focused on the core architecture and counter-intuitive behaviors of the JavaScript programming language. It provides a comprehensive collection of language edge cases, syntax anomalies, and runtime inconsistencies that challenge standard developer assumptions. By grounding these examples in the official ECMAScript specification, the repository serves as a guide for understanding the underlying mechanics of the language. The project distinguishes itself by cataloging specific instances of type coercion, operator precedence

Docker: Printable Quick Reference

On-premises conversational RAG with configurable containers

Run Mixtral-8x7B models in Colab or consumer desktops

gpt-neox is a distributed training system and framework for building large-scale autoregressive language models. It implements the transformer architecture and provides a toolkit for training models with billions of parameters by distributing weights across compute clusters. The framework distinguishes itself through extensive support for distributed model parallelism, including pipeline and sequence parallelism, to overcome single-device memory limits. It further supports sparse model architectures using a mixture of experts system with Sinkhorn-based routing. The project covers a broad ran

This project is a comprehensive reference guide and cheat sheet for the Docker CLI. It provides a structured collection of commands and documentation to help users manage container lifecycles, build images, and handle registries. The documentation specifically covers the orchestration of multi-container applications using Docker Compose and the management of scalable services across multiple nodes via Docker Swarm. It also includes detailed guides for configuring virtual networks, bridges, and ports to control container communication. The reference surface extends to container image administ