Dockerized Nemotron 3.5 ASR: Better Multilingual Support & Streaming (4.5x CPU Speed)
r/LocalLLaMA top day7 days agoNew ToolA developer on Reddit shared a Dockerized implementation of Nemotron 3.5 ASR, migrating from Parakeet. The system supports over 40 languages and features a native streaming architecture that avoids full-file buffering. Using the onnxruntime-genai backend, it achieves 4.5x real-time speed on CPU, with CUDA support planned but untested.
Transformers.js v4 正式上架 NPM！網頁端 WebGPU AI 迎來重大效能升級★ 85
Hugging Face Blog125 days agoReleaseHugging Face officially published Transformers.js v4 on NPM, marking a major milestone for running local AI models within the JavaScript ecosystem…
Hugging Face 發表 Transformers.js v3：支援 WebGPU、新增多款模型與任務，瀏覽器端 AI 效能迎來百倍提升★ 85
Hugging Face Blog600 days agoReleaseHugging Face has officially launched Transformers.js v3, the most significant update to this web-based machine learning library since its release…
從雲端到開發者：Hugging Face 與微軟深化合作，加速開源 AI 部署★ 75
Hugging Face Blog754 days agoBusinessDuring Microsoft Build 2024, Hugging Face announced a further strategic collaboration with Microsoft, aimed at providing developers with a more seamless…
使用 ONNX Runtime 與 Olive 加速 SD Turbo 和 SDXL Turbo 推論★ 75
Hugging Face Blog881 days agoTutorialSD Turbo and SDXL Turbo are single-step/few-step text-to-image models from Stability AI, with their core innovation being Adversarial Diffusion Distillation…
使用 ONNX Runtime 加速超過 130,000 個 Hugging Face 模型★ 75
Hugging Face Blog984 days agoNew ToolHugging Face officially announced a deep collaboration with Microsoft to integrate ONNX Runtime (ORT) into the Hugging Face ecosystem. This partnership enables…
使用 Transformers.js 開發機器學習驅動的網頁遊戲★ 75
Hugging Face Blog1,075 days agoTutorialThis official Hugging Face blog post explores in depth how to use the Transformers.js library to run machine learning (ML) models directly in the browser…
Optimum + ONNX Runtime：讓 Hugging Face 模型訓練更簡單、更快速★ 75
Hugging Face Blog1,237 days agoReleaseAs the scale of deep learning models (such as Transformers) continues to grow, training these models demands enormous computational resources and time. To help…
加速 Document AI：Hugging Face 提升多模態文件理解模型的推論效率★ 70
Hugging Face Blog1,301 days agoTutorial"Document AI" is a key driver of enterprise digital transformation in recent years, aimed at automating the processing of unstructured documents such as…
使用 Hugging Face Optimum 將 Transformers 模型轉換為 ONNX 格式
Hugging Face Blog1,453 days agoTutorialWhen deploying Transformer models in production, latency and throughput are typically the key factors determining the quality of the user experience. ONNX…
使用 Optimum 與 Transformers Pipelines 加速模型推論★ 75
Hugging Face Blog1,496 days agoReleaseWhen deploying Transformer models in production, reducing inference latency and increasing throughput while keeping computational costs under control has…
案例研究：使用 Hugging Face Infinity 與現代 CPU 實現毫秒級延遲
Hugging Face Blog1,613 days agoNew ToolThis case study focuses on the performance of "Hugging Face Infinity" — Hugging Face's high-performance inference container solution — on modern CPUs…
在 CPU 上擴展 BERT 推論效能（第一部分）
Hugging Face Blog1,881 days agoTutorialIn many real-world enterprise production environments, although GPUs offer extremely high throughput for deep learning inference, CPUs remain indispensable due…
Hugging Face 如何為 API 客戶將 Transformer 推理速度提升 100 倍
Hugging Face Blog1,973 days agoReleaseIn this technical blog post, the Hugging Face team reveals in detail how they achieved up to 100x speedup in inference for Transformer models for customers of…