The DIY Revolution: ETH Zurich’s CyberRunner – A Breakthrough in Robotics for Everyone
The research team at ETH Zurich has achieved a groundbreaking success in the field of...
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Author: Maker
ComfyUI for professional stable diffusion workflows – installation and configuration
I am still fascinated by the topic of stable diffusion and image generation. In order to make some...
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Stable Video Diffusion: Creating creative video clips with AI made easy
Stability AI, the innovative startup behind the fascinating image AI Stable Diffusion, has...
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Chatbot Llama 2 70B – run locally in a jupyter notebook
With this article I would like to help you to run locally under Ubuntu 22.04 Llama 2 in the 70B...
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AnyLabeling – installation guide and experience report
A lot of data and matching labels are very important for training neural networks. Therefore,...
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Strategie und Aufbau der eigenen Open-Source-Infrastruktur
Eigene LLMs betreiben, unabhängig von der Cloud. Von der Hardware bis zum laufenden System.
Jetzt bei Amazon bestellenRoboter-Autos mit dem ESP32
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Vom ersten Chassis bis zur WLAN-Steuerung. Schritt für Schritt zum eigenen Roboter-Auto.
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- Local Voice Agent: Wiring ASR, LLM and TTS into a Loop with NVIDIA Pipecat Locally
Every building block is now available locally: ASR (Parakeet, Canary), TTS (Magpie), an LLM via my Ollama server and the orchestrator (NAT, Part 5). Now I’m connecting them into a continuous, interruptible speech loop. This will be my first small local voice agent. What I’m aiming for is a kind of general-purpose agent: I speak,… Read more: Local Voice Agent: Wiring ASR, LLM and TTS into a Loop with NVIDIA Pipecat Locally - NVIDIA NeMo Agent Toolkit (NAT): set up the agent orchestrator locally
The two halves of a voice agent are in place: with Parakeet (Part 2) and Canary (Part 3) the agent listens, with Magpie (Part 4) it answers. What’s still missing is the brain: the layer that turns recognized text into a decision and triggers the matching answer or action. That’s exactly what I take on… Read more: NVIDIA NeMo Agent Toolkit (NAT): set up the agent orchestrator locally - NVIDIA Magpie TTS locally: German speech output as a microservice
The speech recognition is in place: with Parakeet (Part 2) and Canary (Part 3) I covered the input direction, speech to text, natively on NVIDIA. Now comes the opposite direction, the voice output. In this post I run NVIDIA Magpie TTS as a local NIM and have German text read aloud naturally. This is the… Read more: NVIDIA Magpie TTS locally: German speech output as a microservice - NVIDIA Canary locally: multilingual speech recognition and translation as a NIM
In Part 2 I set up Parakeet as a streaming-capable ASR NIM for German and ran it as a live service with low latency. In this post I take on the sister model: NVIDIA Canary as a NIM. Canary does not shine at latency but at accuracy, and it can do something Parakeet cannot: translate.… Read more: NVIDIA Canary locally: multilingual speech recognition and translation as a NIM - NVIDIA NIM locally: running German speech recognition as a microservice
In my last post I ran NVIDIA Nemotron ASR Streaming directly with NeMo locally. That was the “bare” route via the framework. In this post I go one step further and dive into NVIDIA NIM. NIM stands for NVIDIA Inference Microservices, the microservice variant NVIDIA uses to ship its models as ready-made, optimized containers. The… Read more: NVIDIA NIM locally: running German speech recognition as a microservice
The tutorial offers a clear and practical guide for setting up and running the Tensorflow Object Detection Training Suite. Could…
This works using an very old laptop with old GPU >>> print(torch.cuda.is_available()) True >>> print(torch.version.cuda) 12.6 >>> print(torch.cuda.device_count()) 1 >>>…
Hello Valentin, I will not share anything related to my work on detecting mines or UXO's. Best regards, Maker
Hello, We are a group of students at ESILV working on a project that aim to prove the availability of…