Open-source text-to-speech library with a 1.7B 1-bit speech model and lightweight ONNX models that run on CPU.
A Python-embedded domain-specific language and TVM-based compiler for writing high-performance GPU, CPU, and NPU kernels.
A library of model optimization techniques (quantization, pruning, distillation, NAS, speculative decoding, sparsity) that exports compressed checkpoints for inference frameworks.