Llms

Generative AI, Large Language Models(LLMs), Prompt Engineering, Fine-Tune AI Model,GPT models, Hugging Face,Google Colab

Mastering LLM Parallelism: Scale Large Language Models with DeepSpeed & Multi-GPU Systems

Become an NVIDIA Certified Generative AI Specialist (NCA-GENL Exam Prep)

Run open large language models like Gemma, Llama or DeepSeek locally to perform AI inference on consumer hardware.

Discover the World of Large Language Models with Open Source Models like LLama3 and ChatGPT

Transform Your LLMs Knowledge From an Interested Field Observer to a Well-equipped NLP Developer

Run open large language models like Gemma, Llama or DeepSeek locally to perform AI inference on consumer hardware.

Learn how to connect Langchain to OpenAI to work with LLMs in Python through practical examples.

Mastering AI Development: Hands-On Projects & Deep Insights with Python, LangChain & OpenAI's Advanced LLMs

The advancement of Large Language Models (LLMs) has revolutionized the field of Natural Language Processing in recent years. Models like BERT, T5, and ChatGPT have demonstrated unprecedented performance on a wide range of NLP tasks, from text classification to machine translation. Despite their impressive performance, the use of LLMs remains challenging for many practitioners. The sheer size of these models, combined with the lack of understanding of their inner workings, has made it difficult for practitioners to effectively use and optimize these models for their specific needs.