Easily fine-tune, evaluate and deploy Gemma 4, Qwen3.5, Qwen3.6, gpt-oss, DeepSeek-R1, or any open source LLM / VLM!

Federated Learning for LLMs.

Upload your data → Get a fine-tuned SLM. Free.

The official implementation of "A Language Modeling Approach to Diacritic-Free Hebrew TTS"

Automatically exported from code.google.com/p/audiotools

'Zest' Natural Language to CLI commands tool from Spicy Lemonade

Azure IoT Operations with Edge AI in-a-Box

Fine-tuning open-source large and small instruct/chat language models (LLMs & SLMs) from the Hugging Face Model Hub using public datasets.

Tool-calling AI agents that run locally.

Kurtis is a fine-tuning, inference and evaluation tool built for SLMs (Small Language Models), such as Huggingface's SmolLM2.

This project demonstrates how to evaluate the use of LLMs and SLMs for extracting structured data from documents using .NET

🧳 SayHalo – AI-powered (gen-ai) SLM Aggregator for seamless chat experience. 💬🤖 Built with Next.js, TypeScript, Tailwind & Resend. ⚡✨ Early access available now! 🔥

[ICLR 2026 Accepted paper] BeyondBench: Contamination-Resistant Evaluation of Reasoning in Language Models

AetherArena- Agentic Desktop Assistant

SLM-T-Q-Relay implements a query routing mechanism within a tree of small language models, where each node either answers or forwards queries to the most relevant model.

This repository documents the journey of building a Small Language Model (SLM) from the ground up using Python and PyTorch. The model is a decoder-only Transformer, trained on a custom corpus of academic papers and articles focused on artificial intelligence theory.

I'm lazy... That's why I'm doing this...

Accoutre aims to equip SLMs with tools and measure the gains - A zero-build playground for skill orchestration and benchmarking.

A modular, fully local LLM orchestration framework that dynamically routes user queries to specialized LoRA adapters while maintaining a single base model instance in memory. This system is designed for efficiency, extensibility, and offline capability, enabling intelligent task-specific responses without relying on external APIs.

run AI models anywhere