AI Pipeline – AI Pipeline Image App Setup and Operation Part 1-2
In the previous chapter, you learned about the SWAGGER API, which can be used to test the neural...
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Tag: no code
AI Pipeline – Tensorflow Object Detection Training GUI – SWAGGER API testing the neural network
After the previous article explained how to train a neural network with your own training data,...
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AI Pipeline – Tensorflow Object Detection Training GUI – Usage
In the previous article you have configured and installed the Training Suite on your computer. In...
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AI Pipeline – Tensorflow Object Detection Training GUI Run
The BMW Tensorflow Object Detection Training GUI is already installed on your computer and you...
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AI Pipeline – Tensorflow-Object-Detection-Training-GUI Installation
The BMW Tensorflow Object Detection Training GUI is the heart of the No-Code AI pipeline. It is...
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AI Pipeline – Labeltool Lite Handling
This article is about how to use the Labeltool Lite. In the previous article you have prepared the...
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AI Pipeline – Labeltool Lite Preparation
After the successful installation of the Labelingtool Lite, as described in the previous article,...
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AI Pipeline – Labeltool Lite Installation
After you have updated your Ubuntu installation and installed the additional software packages, it...
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AI Pipeline – Software Installation of the No-Code AI Pipeline
After you have already worked through the introduction to the topic of which hardware do I need...
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AI Pipeline – Hardware Example Configurations
With the first part around the topic hardware now follows the second part which presents concrete...
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AI Pipeline – Hardware Basics
The knowledge and hardware requirements for using the No-Code AI pipeline are not particularly...
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AI Pipeline – The Three Components
With the three modules of the No-Code AI Pipeline, it is possible for you to directly enter the...
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- Open-WebUi – Ollama
After I had already installed Ollama as a server and had written one or two Python programs that used the API interface and the underlying language models, Open-WebUi for Ollama aroused my interest. That’s how this article was created, which describes how you could install and use Open-WebUi. In the lower part, after setting up… Read more: Open-WebUi – Ollama - RAG Chat-Applikation – Langchain + Ollama + Streamlit
In terms of technical requirements and architecture, this solution is not very complex and is therefore ideal for getting started with large language models. It is also guaranteed to give you an initial sense of achievement very quickly. All the components used can be easily installed and combined with each other. I have followed the… Read more: RAG Chat-Applikation – Langchain + Ollama + Streamlit - Ollama Ubuntu installation and configuration
This short guide is made up of several articles and takes you step by step from the installation to the finished application. First of all, the instructions are structured so that Ollama is installed. Ollama is used as a server that provides the various language models. The big advantage of Ollama (https://github.com/ollama/ollama) is that it… Read more: Ollama Ubuntu installation and configuration - Installation of Anaconda on Ubuntu LTS version
I wrote this post because I always install my programs and associated packages such as drivers in a virtual Anaconda environment and it is therefore important that you understand how Anaconda is set up under Ubuntu. The big advantage that comes with this is that you can simply delete the Anaconda environments with your installation… Read more: Installation of Anaconda on Ubuntu LTS version - CUDA driver installation under Ubuntu
I most often use Ubuntu as my operating system when it comes to trying out new developments in the field of generative AI such as stable diffusion applications or in the area of large language models (LLM). I benefit from the fact that I have an NVIDIA A6000 graphics card installed in my computer which,… Read more: CUDA driver installation under Ubuntu