Build high-performance AI models with modular building blocks
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Any model. Any hardware. Zero compromise. Built with @ziglang / @openxla / MLIR / @bazelbuild
A deep learning framework built on an autograd engine with high level abstractions and low level control.
A deep learning framework built on an autograd engine with high level abstractions and low level control.
Ongoing research training transformer models at scale
Foundation Architecture for (M)LLMs
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.
