Search Results for "runtime onnx"
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9 projects for "runtime onnx" with 1 filter applied:
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kokoro-onnx
TTS with kokoro and onnx runtime
kokoro-onnx is a text-to-speech toolkit that wraps the Kokoro neural TTS model in an easy-to-use ONNX Runtime interface, so you can generate speech from Python with minimal setup. It focuses on running efficiently on commodity hardware, including macOS with Apple Silicon, while still delivering near real-time performance for many use cases. The project ships prebuilt model files and a simple example script, so you can go from installation to producing an audio.wav file in just a few steps. ... -
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ort
Fast ML inference & training for ONNX models in Rust
ort is a high-performance Rust library that provides bindings to ONNX Runtime, enabling developers to run machine learning inference and training workflows directly within Rust applications using the standardized ONNX model format. It is designed to bridge the gap between modern machine learning frameworks and systems programming by offering a safe, ergonomic API for executing models originally built in ecosystems like PyTorch, TensorFlow, or scikit-learn. -
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rust-bert
Rust native ready-to-use NLP pipelines and transformer-based models
...It allows developers to run state-of-the-art NLP models like BERT, GPT-2, and DistilBERT directly within Rust applications while maintaining high performance and memory efficiency. The library integrates with Rust machine learning infrastructure using crates such as tch-rs and ONNX Runtime for model execution. It also includes tokenization utilities, model architectures, and task-specific pipelines that simplify the development of NLP applications. Because Rust is known for its safety and performance, this project enables developers to deploy modern NLP models in production systems written in Rust. -
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Microduck RL
RL training environments for Microduck (mjlab)
...The repository includes tasks for walking, standing up, sitting, kicking, rolling, skating, crouching, and other physical behaviors. Its sim-to-real setup models actuator physics, backlash, domain randomization, and reward design. Trained policies can be exported to ONNX and deployed through the separate Microduck runtime. Training normally uses CUDA hardware, while supported workflows can offload jobs to Hugging Face Jobs when a local GPU is unavailable. -
Train ML Models With SQL You Already KnowBuild and deploy ML models using familiar SQL. Automate data prep with built-in Gemini. Query 1 TB and store 10 GB free monthly.
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DragonianVoice
C++ inference library for multiple SVC/TTS
...It uses ONNX Runtime and other backends to accelerate inference, with notes on how different execution providers such as CUDA or DirectML affect operator support and numerical stability. Recent versions integrate with fish-speech via a dedicated fish-speech.cpp subproject using ggml. -
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Supertonic
Lightning-fast, on-device TTS, running natively via ONNX
Supertonic is a lightning-fast, on-device text-to-speech system built around ONNX Runtime for maximum speed and portability. It focuses on running entirely locally, eliminating the need for cloud APIs and providing low latency and strong privacy guarantees, even on constrained devices like Raspberry Pi boards and e-readers. The core model is highly compact at around 66 million parameters, yet benchmarks show it can generate speech up to 167× faster than real time on modern consumer hardware and significantly outpace popular cloud TTS APIs in throughput and real-time factor. ... -
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ComfyUI InstantID
Native InstantID support for ComfyUI
...Unlike other implementations, it does not rely on diffusers and instead integrates InstantID directly into ComfyUI workflows. The extension is designed for SDXL and uses InsightFace, ONNX Runtime, the antelopev2 face model, an InstantID model, and a ControlNet model. It lets users generate images guided by a reference face while controlling pose through face keypoints. The project includes basic workflows, video guidance, noise injection options, additional ControlNet support, IPAdapter styling, Multi-ID workflows, and an advanced node for separate model and ControlNet weights. ... -
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Matcha-TTS
A fast TTS architecture with conditional flow matching
Matcha-TTS is a non-autoregressive neural text-to-speech architecture that uses conditional flow matching to generate speech quickly while maintaining natural quality. It models speech as an ODE-based generative process, and conditional flow matching lets it reach high-quality audio in only a few synthesis steps, which greatly reduces latency compared to score-matching diffusion approaches. The model is fully probabilistic, so it can generate diverse realizations of the same text while still... -
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KotlinDL
High-level Deep Learning Framework written in Kotlin
KotlinDL is a high-level Deep Learning API written in Kotlin and inspired by Keras. Under the hood, it uses TensorFlow Java API and ONNX Runtime API for Java. KotlinDL offers simple APIs for training deep learning models from scratch, importing existing Keras and ONNX models for inference, and leveraging transfer learning for tailoring existing pre-trained models to your tasks. This project aims to make Deep Learning easier for JVM and Android developers and simplify deploying deep learning models in production environments. -
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