PyTorch

Fine-Tuning LLaMA 2 Models with a single GPU and OVHcloud

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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speech to text app image3

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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speech to text app image2

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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speech to text app image1

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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streamlit app for eda and interactive prediction

Deploy a custom Docker image for Data Science project – Streamlit app for EDA and interactive prediction (Part 2)

A guide to deploy a custom Docker image for a Streamlit app with AI Deploy. Welcome to the second article concerning custom Docker image deployment. If you haven’t read the previous one, you can read it on the following link. It was about Gradio and sketch recognition. When creating code for a Data Science project,

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