How to serve LLMs with vLLM and OVHcloud AI Deploy
In this tutorial, we will learn how to serve Large Language Models (LLMs) using vLLM and the OVHcloud AI Products.
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Understanding Image Generation: A Beginner’s Guide to Generative Adversarial Networks
How to train a generative adversarial network (GAN) to generate images ?
How to train a DCGAN ?
How GAN and DCGAN work ?
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Fine-Tuning LLaMA 2 Models using a single GPU, QLoRA and AI Notebooks
In this tutorial, we will walk you through the process of fine-tuning LLaMA 2 models, providing step-by-step instructions. All the code related to this article is available in our dedicated GitHub repository. You can reproduce all the experiments with OVHcloud AI Notebooks. Introduction On July 18, 2023, Meta released LLaMA 2, the latest version of
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Image segmentation: Train a U-Net model to segment brain tumors
brain tumor segmentation tutorial with BraTS2020 dataset and U-Net
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How to build a Speech-To-Text Application with Python (3/3)
A tutorial to create and build your own Speech-To-Text Application with Python. At the end of this third article, your Speech-To-Text Application will offer many new features such as speaker differentiation, summarization, video subtitles generation, audio trimming, and others! Final code of the app is available in our dedicated GitHub repository. Overview of our final
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How to build a Speech-To-Text Application with Python (2/3)
A tutorial to create and build your own Speech-To-Text Application with Python. At the end of this second article, your Speech-To-Text application will be more interactive and visually better. Indeed, we are going to center our titles and justify our transcript. We will also add some useful buttons (to download the transcript, to play with
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How to build a Speech-To-Text application with Python (1/3)
A tutorial to create and build your own Speech-To-Text application with Python. At the end of this first article, your Speech-To-Text application will be able to receive an audio recording and will generate its transcript! Final code of the app is available in our dedicated GitHub repository. Overview of our final app Overview of our
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