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Tutoriale AI

Rămâneți la curent cu cele mai recente tehnici, instrumente și cercetări în inteligența artificială. Tutorialele noastre de AI vă vor ghida prin modele de învățare automată dificile.
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Understanding Prompt Tuning: Enhance Your Language Models with Precision

Prompt tuning is a technique used to improve the performance of a pre-trained language model without modifying the model’s internal architecture.
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Dimitri Didmanidze

19 mai 2024

Vertex AI Tutorial: A Comprehensive Guide For Beginners

Master the fundamentals of setting up Vertex AI and performing machine learning workflows.
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Bex Tuychiev

17 mai 2024

Getting Started With Mixtral 8X22B

Explore how Mistral AI's Mixtral 8X22B model revolutionizes large language models with its efficient SMoE architecture, offering superior performance and scalability.
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Bex Tuychiev

15 mai 2024

How to Use the Stable Diffusion 3 API

Learn how to use the Stable Diffusion 3 API for image generation with practical steps and insights on new features and enhancements.
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Kurtis Pykes

13 mai 2024

Fine-Tune and Run Inference on Google's Gemma Model Using TPUs for Enhanced Speed and Performance

Learn to infer and fine-tune LLMs with TPUs and implement model parallelism for distributed training on 8 TPU devices.
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Abid Ali Awan

13 mai 2024

Phi-3 Tutorial: Hands-On With Microsoft’s Smallest AI Model

Learn about Microsoft’s Phi-3 language model, including its architecture, features, applications, installation, setup, integration, optimization, and fine-tuning.
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Zoumana Keita

11 ianuarie 2025

Databricks DBRX Tutorial: A Step-by-Step Guide

Learn how Databricks DBRX—an open-source LLM can handle complex tasks and generate intelligent results.
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Laiba Siddiqui

9 mai 2024

What is Data Labeling And Why is it Necessary for AI?

Explore the critical role of data labeling in AI, including its definition, necessity, techniques, challenges, and best practices.
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Kurtis Pykes

9 mai 2024

Run LLMs Locally: 6 Simple Methods

Run LLMs locally (Windows, macOS, Linux) by using these easy-to-use LLM frameworks: Ollama, LM Studio, vLLM, llama.cpp, Jan, and llamafile.
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Abid Ali Awan

12 ianuarie 2026

Reinforcement Learning: An Introduction With Python Examples

Learn the fundamentals of reinforcement learning through the analogy of a cat learning to use a scratch post.
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Bex Tuychiev

2 mai 2024

How to Improve RAG Performance: 5 Key Techniques with Examples

Explore different approaches to enhance RAG systems: Chunking, Reranking, and Query Transformations.
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Eugenia Anello

12 aprilie 2024