Results for “local models” — 264

📇 ☁️ - AI-powered web search server using Perplexity Sonar models with source citations. Zero-install setup via NPX.

Accessible large language models via k-bit quantization for PyTorch.

QwenLM/Qwen3

github.com

Qwen3 is the large language model series developed by Qwen team, Alibaba Cloud.

🐍 ☁️ - Bridge to OpenAI API. Access GPT-4, GPT-4o and other OpenAI models through MCP.

 🐍 🏠 - Reversibly compress a large tool output to a recoverable 8-hex handle over stdio, expand it on demand, and report a local token/dollar savings ledger.

📇 🏠 🍎 🪟 🐧 - Filesystem-direct Obsidian MCP server with low context-tax. Reads your vault directly from disk — no Local REST API plugin required. ~575× smaller payloads than the REST plugin. 8 tools. npx -y obsidian-mcp-seekstone (also: npx -y seekstone)

 🐍 🏠 🍎 🪟 🐧 - Converts local PDFs into source-linked, card-based standalone HTML readers with notes, highlights, and static publishing.

A collection of papers and resources about aligning large language models (LLMs) with human.

a suite of libraries for interpreting machine learning models according to their algebraic structure. [Deprecated]

> A delightful machine learning tool that allows you to train/fit, test and use models without writing code

Interactive reports to analyze machine learning models during validation or production monitoring.

Ignite your models into blazing-fast machine learning APIs with a modern framework.

Fast Neural Networks framework built on top of Metal. Supports TensorFlow models.

a chat interface crafted with llama.cpp for running Alpaca models. No API keys, entirely self-hosted!

Open-source Python tools for testing and evaluating models, vector DBs, and prompts.

This repository contains code to quantitatively evaluate instruction-tuned models such as Alpaca and Flan-T5 on held-out tasks.

 📇 🏠 - Zero-trust local PII and secrets masking server for Cursor, Windsurf, and Claude Desktop. npx pii-masking-run

Serve, optimize and scale PyTorch models in production (Archived)

An Extensible Toolkit for Finetuning and Inference of Large Foundation Models

Using Low-rank adaptation to quickly fine-tune diffusion models.

🚀 A simple way to train and use PyTorch models with multi-GPU, TPU, mixed-precision.

A framework to connect a flow of ML models by applying graph theory.

A trend starts from "Chain of Thought Prompting Elicits Reasoning in Large Language Models.

A production-ready library for multicalibration, fairness, and bias correction in machine learning models.

A PyTorch-based framework to train and validate the models producing high-quality embeddings.

A comparative framework for multimodal recommender systems with a focus on models leveraging auxiliary data.

Python-free Rust inference server for NLP models with OpenAI API compatibility and hot model swapping.

A powerful tool for creating high-quality training datasets for Large Language Models

An Efficient and User-Friendly Scaling Library for Reinforcement Learning with Large Language Models.

simplifies the evaluation of LLMs by providing a unified microservice to access and test multiple AI models.

An Open-Ended Embodied Agent with Large Language Models !GitHub Repo stars

🐍 ☁️ - Bridge to Google Gemini API. Access Gemini Pro and Flash models through MCP.

 🦀 🏠 🪟 - Windows-native full-disk search over file names, document contents, and OCR'd screenshot text, exposed to AI agents via a read-only local MCP server.

 🦀 🏠 🍎 🪟 🐧 - Local full-text code search for AI coding agents. Trigram-indexed, sub-100ms queries across large codebases, offline, 18 languages.

a service for deployment Apache Spark MLLib machine learning models as realtime, batch or reactive web services.

> Curated collection of the neural networks, transformers and models that make your machine learning work faster and more effective.