AirLLM 2.8T LLM inference with single 4GB GPU
FastAPI framework, high performance, easy to learn, fast to code, ready for production
A unified library of SOTA model optimization techniques like quantization, distillation, pruning, neural architecture search, speculative decoding, etc. It compresses deep learning models for downstream deployment frameworks like TensorRT-LLM, TensorRT, vLLM, etc. to optimize inference speed.
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A secure Python sandbox, written in Rust, for code written by AI.
Integrate cutting-edge LLM technology quickly and easily into your apps
Open-source implementation of a substantial portion of the API of Apple CryptoKit suitable for use on all Swift supported platforms.
Static Code Analysis for R