ONNX
PulseAugur coverage of ONNX — every cluster mentioning ONNX across labs, papers, and developer communities, ranked by signal.
5 天有情绪数据
-
AI source separation models converted for real-time DJ software use
Anmol Mishra presented a method for converting source separation AI models into the ONNX format. This conversion enables real-time application of these models within DJ software. The presentation, part of the Audio Deve…
-
ONNX framework speeds up Sentence-BERT inference
This article explores how the ONNX framework can accelerate inference times for Sentence-BERT (SBERT) models, which are commonly used for generating sentence embeddings. The author demonstrates this by converting the `a…
-
Supertone ships Supertonic 3 TTS with 31 languages, inline expressiveness
Supertone has launched Supertonic 3, an updated on-device text-to-speech model that now supports 31 languages, a significant increase from its previous five. This new version boasts improved accuracy, reduced errors lik…
-
Hugging Face releases open multilingual embedding models with 32K context
Hugging Face has released Granite Embedding Multilingual R2, a suite of open-source multilingual embedding models. The release includes a 97M-parameter compact model that leads in retrieval quality among open models und…
-
ONNX format powers Microsoft AI, enabling cross-framework compatibility
The article discusses the often-overlooked AI format known as ONNX (Open Neural Network Exchange). ONNX serves as a crucial intermediary, enabling interoperability between different AI frameworks and hardware accelerato…
-
Source Separation Models Converted to ONNX for DJ Software
Anmol Mishra presented on converting source separation models to ONNX format for real-time use in DJ software. The presentation, shared via YouTube links across various Mastodon instances, focused on the technical aspec…
-
Spring AI and JEP 489 enable faster, cheaper local LLM re-ranking
This article details a method for optimizing Retrieval-Augmented Generation (RAG) performance by performing local re-ranking of retrieved documents. It advocates for using Java's JEP 489 Vector API for SIMD-accelerated …
-
AI models advance plant disease detection with new datasets and efficient distillation
Researchers have developed new methods for plant leaf disease classification to aid in early detection and treatment. One approach involves training a new base model using the DenseNet201 architecture on a custom datase…
-
Object detection models show mixed robustness to quantization and input degradations
A new study investigates how post-training quantization (PTQ) affects the robustness of YOLO object detection models when faced with real-world input degradations like noise and blur. Researchers evaluated various preci…
-
Apple explores ONNX in browser for AI Gaussian Splats
Apple is exploring the use of ONNX within a web browser to enable AI-powered Gaussian Splats. This initiative appears on GitHub, aiming to integrate advanced AI capabilities into web applications. The project is highlig…
-
AI model predicts stuttering events from audio, deploys on-device
Researchers have developed a new Convolutional Neural Network (CNN) model capable of predicting upcoming stuttering events from short audio clips. The 616K-parameter model, trained on the SEP-28k dataset, demonstrates a…
-
KittenML releases lightweight, CPU-optimized TTS models
KittenML has released version 0.8 of its open-source text-to-speech library, Kitten TTS. This update introduces three new models with parameter counts of 15M, 40M, and 80M, offering sizes from 25MB to 80MB. The library …
-
PHP-ORT brings machine learning inference to PHP developers
A new infrastructure project called PHP-ORT aims to bring machine learning inference capabilities directly to PHP, the server-side language used by a significant portion of the web. This development seeks to empower mil…
-
Glowstick crate adds type-level tensor shape checking to Rust
Glowstick is a new Rust crate designed to enhance tensor manipulation by integrating shape checking directly into the type system. This approach aims to make tensor operations safer and more intuitive, particularly for …
-
ONNX standardizes AI model interoperability for seamless framework integration
The Open Neural Network Exchange (ONNX) is an open-source format designed to facilitate interoperability between different machine learning frameworks. It defines a computation graph model and standard operators, primar…
-
Optimizing Transformer Inference: Techniques for Faster, Cheaper Large Models
Large transformer models present significant inference challenges due to their substantial memory footprint and computation costs, which scale quadratically with input length. Researchers and practitioners are exploring…