Tutoriels sur l'IA

Learn how fine-tuning large language models (LLMs) improves their performance in tasks like language translation, sentiment analysis, and text generation.

Discover everything you need to know about LMQL, short for Language Models Query Language, an innovative programming language for LLMs.

Learn an end-to-end workflow to monitor any model in your Jupyter notebook in production environments.

Understanding the Phi-2 model and learning how to access and fine-tune it using the role-play dataset.

Step-by-step guide for building LLM-powered Chatbot on your own custom data, leveraging RAG techniques using OpenAI and Pinecone in Python.

Gemini defines a family of multimodal LLMs capable of understanding texts, images, videos, and audio. It’s also said to be capable of performing complex tasks in math and physics, as well as being able to generate high-quality code in several programming languages.

This tutorial dives into the Databricks approach to AI & Machine Learning in the Databricks Lakehouse and introduces its latest features.

A complete guide to using the SOLAR-10.7B fine-tuned model for instruction-based tasks in a real-world scenario.

Learn how to use Gemini Python API and its various functions to build AI-enabled applications for free.

Explore the groundbreaking technique of Low-Rank Adaptation (LoRA) in our full guide. Discover how LoRA revolutionizes the fine-tuning of Large Language Models.

Dive into the essentials of backpropagation in neural networks with a hands-on guide to training and evaluating a model for an image classification use scenario.

Learn everything about Zephyr-7B, including its training, how to access it, and how to fine-tune it on a custom database using free Kaggle GPUs.