Deploy and serve AI models for applications, APIs, or production workloads.
Showing 12 of 30 tools
Platform for running large language models locally on a computer
🤗 Transformers: the model-definition framework for state-of-the-art machine learning models in text, vision, audio, and multimodal models, for both inference and training.
A high-throughput and memory-efficient inference and serving engine for LLMs
Unified Efficient Fine-Tuning of 100+ LLMs & VLMs (ACL 2024)
The fastest, litest AI Gateway. Rust core with Python SDK. Call 100+ LLM APIs in OpenAI (or native) format with cost tracking, guardrails, load balancing, and logging [Bedrock, Azure, OpenAI, Anthropic, OpenAI, VertexAI, vLLM, Nvidia NIM]
LocalAI is the open-source AI engine. Run any model - LLMs, vision, voice, image, video - on any hardware. No GPU required.
🦍 The API and AI Gateway
Ray is an AI compute engine. Ray consists of a core distributed runtime and a set of AI Libraries for accelerating ML workloads.
Making large AI models cheaper, faster and more accessible
Langchain-Chatchat (formerly Langchain-ChatGLM) is a RAG and Agent application built with LangChain and language models such as ChatGLM, Qwen, and Llama, designed for local knowledge-based LLM applications.
Pretrain, finetune ANY AI model of ANY size on 1 or 10,000+ GPUs with zero code changes.
SGLang is a high-performance serving framework for large language models and multimodal models.
