(Realtime) Temporal Convolutions in PyTorch

Streamable Text-to-Speech model using a language modeling approach, without vector quantization

Dual-model speech AI toolkit for speaker verification and speaker-aware diarization, with streaming inference, meeting analysis, long-audio monitoring, and speaker-bank integration.

Pure PyTorch + 🤗 Transformers reimplementation of Megalodon (CEMA + chunked attention) - readable, hackable, no CUDA kernels required

World's most deployable time series foundation model — 200K-6.5M params, zero-shot forecasting, streaming RNN inference, ONNX edge deployment, runs on Raspberry Pi

Open ML systems platform for training, profiling, evaluating, and serving AI models.

Lossless AI model compression - ~34% smaller with bit-identical weights; the autopilot profiles your machine, picks the highest fidelity that runs, and streams models bigger than your RAM.

Don't Think It Twice: Exploit Shift Invariance for Efficient Online Streaming Inference of CNNs

CascadeLUT: Information-Ordered Streaming Inference for Bandwidth-Constrained FPGAs [FPL'26]

CPU-native inference runtime. Local-propagation paradigm: the active region pays the cost, not the field. Bit-exact across architectures. Validated for streaming anomaly detection and audio VAD.

Streaming version of S4ND-U-Net

Real-time music-genre classification: spectrogram CNN, ONNX-optimised, served as a streaming/chunked classifier with PyTorch-vs-ONNX benchmarks. Track-aware GTZAN eval.