open-source-llm

Run any open-source LLMs, such as DeepSeek and Llama, as OpenAI compatible API endpoint in the cloud.

Running Llama 2 and other Open-Source LLMs on CPU Inference Locally for Document Q&A

LLM-PowerHouse: Unleash LLMs' potential through curated tutorials, best practices, and ready-to-use code for custom training and inferencing.

Open-source local AI SDK - run AI on-device with no cloud, no API keys. Supports GGUF, RAG, image, music, and video generation, speech-to-text, P2P inference, and more. Cross-platform: Linux, macOS, Windows, Android, iOS.

LLM (Large Language Model) FineTuning

🏗️ Fine-tune, build, and deploy open-source LLMs easily!

LLMs and Machine Learning done easily

A list of LLMs Tools & Projects

This is a PHP library for Ollama. Ollama is an open-source project that serves as a powerful and user-friendly platform for running LLMs on your local machine. It acts as a bridge between the complexities of LLM technology and the desire for an accessible and customizable AI experience.

Run Open Source/Open Weight LLMs locally with OpenAI compatible APIs

Samples on how to build industry solution leveraging generative AI capabilities on top of SAP BTP and integrated with SAP S/4HANA Cloud.

EmbeddedLLM: API server for Embedded Device Deployment. Currently support CUDA/OpenVINO/IpexLLM/DirectML/CPU

Pair Claude Desktop on Anthropic with Claude Code routed through Ollama. Visual walkthrough + copy-paste prompt that cuts your Claude Code bill ~90%.

GPU-accelerated LLaMA inference wrapper for legacy Vulkan-capable systems a Pythonic way to run AI with knowledge (Ilm) on fire (Vulkan).

A native macOS lab for teaching tiny language models to think — build the architecture, train the weights, and watch a small LLM emerge from scratch, locally on Apple Silicon with custom data, tokenizers, checkpoints, and MLX acceleration.

An autonomous agentic pipeline that finds, proves, and patches real C memory-safety vulnerabilities end-to-end using a single 7B open-source LLM (Qwen2.5-Coder) on vLLM, with AddressSanitizer as a ground-truth oracle.

md2LLM enables fine-tuning of open-source language models using personal Markdown files. It includes an observability and management layer for the fine-tuning process, allowing users to generate training data, manage models, and track and store each state of the fine-tuned model.

What LLM inference actually costs. 874 verified price rows across 24 providers, 378 GPU rental rates, 395 cited throughput datapoints, and a self-hosting break-even model. Every number carries a source URL, a retrieval date, and passed a mechanical evidence gate. Dated immutable snapshots. CC BY 4.0.

Read your local files and answer your queries

Weekly tracker of LLM rankings from the official LMArena dataset: CSV history, auto-generated trend charts (frontier race, open-weight vs proprietary), updated by GitHub Actions.