Tutorials on Ai Model Training

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  • React
  • Angular
  • Vue
  • Svelte
  • NextJS
  • Redux
  • Apollo
  • Storybook
  • D3
  • Testing Library
  • JavaScript
  • TypeScript
  • Node.js
  • Deno
  • Rust
  • Python
  • GraphQL

6 Fine-Tuning LLM Frameworks Ranked by Speed, Memory, and GPU Needs

Six training frameworks are covered here: Axolotl, DeepSpeed, Megatron-LM, PyTorch Lightning Fabric, Torchtune, and Unsloth. Available benchmarks don't line up across them. Speed comparisons come from reported throughput tests; memory figures reflect documented VRAM ranges for LoRA, QLoRA, and full…
Thumbnail Image of Tutorial 6 Fine-Tuning LLM Frameworks Ranked by Speed, Memory, and GPU Needs
Image of Author Dr. Dipen
Dr. Dipen
I am an AI/ML researcher with 150+ citations and 16 published research papers. I have three tier-1 publications, including Internet of Things (Elsevier), Biomedical Signal Processing and Control (Elsevier), and IEEE Access. In my research journey, I have collaborated with NASA Glenn Research Center, Cleveland Clinic, and the U.S. Department of Energy for various research projects. I am also an official reviewer and have reviewed over 100 research papers for Elsevier, IEEE Transactions, ICRA, MDPI, and other top journals and conferences. I hold a PhD from Cleveland State University with a focus on large language models (LLMs) in cybersecurity, and I also earned a master’s degree in informatics from Northeastern University.
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Fine-Tuning LLM Checklist: 6 Data Failures to Catch Before Your Training Run

The short version: Your SFT run is only as good as the rows you feed it. Most fine-tuning tutorials rush you to the GPU. We'd rather you spend that first stretch on the data, because that's where projects quietly fail. The right dataset is not always the largest one. Review examples for coverage,…
Thumbnail Image of Tutorial Fine-Tuning LLM Checklist: 6 Data Failures to Catch Before Your Training Run
Image of Author Dr. Dipen
Dr. Dipen
I am an AI/ML researcher with 150+ citations and 16 published research papers. I have three tier-1 publications, including Internet of Things (Elsevier), Biomedical Signal Processing and Control (Elsevier), and IEEE Access. In my research journey, I have collaborated with NASA Glenn Research Center, Cleveland Clinic, and the U.S. Department of Energy for various research projects. I am also an official reviewer and have reviewed over 100 research papers for Elsevier, IEEE Transactions, ICRA, MDPI, and other top journals and conferences. I hold a PhD from Cleveland State University with a focus on large language models (LLMs) in cybersecurity, and I also earned a master’s degree in informatics from Northeastern University.
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Optimize RL with TRPO Techniques at Newline

Watch: L4 TRPO and PPO (Foundations of Deep RL Series) by Pieter Abbeel TRPO (Trust Region Policy Optimization) is a cornerstone algorithm in reinforcement learning (RL) that addresses critical challenges like policy instability, sample inefficiency, and safety constraints. By combining a monotonic…
Image of Author Dr. Dipen
Dr. Dipen
I am an AI/ML researcher with 150+ citations and 16 published research papers. I have three tier-1 publications, including Internet of Things (Elsevier), Biomedical Signal Processing and Control (Elsevier), and IEEE Access. In my research journey, I have collaborated with NASA Glenn Research Center, Cleveland Clinic, and the U.S. Department of Energy for various research projects. I am also an official reviewer and have reviewed over 100 research papers for Elsevier, IEEE Transactions, ICRA, MDPI, and other top journals and conferences. I hold a PhD from Cleveland State University with a focus on large language models (LLMs) in cybersecurity, and I also earned a master’s degree in informatics from Northeastern University.
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TRPO vs PPO for RL Success

Reinforcement learning (RL) has seen transformative advancements with the development of Trust Region Policy Optimization (TRPO) and Proximal Policy Optimization (PPO). These algorithms address critical challenges in policy optimization, ensuring stable and efficient learning in complex…
Thumbnail Image of Tutorial TRPO vs PPO for RL Success
Image of Author Dr. Dipen
Dr. Dipen
I am an AI/ML researcher with 150+ citations and 16 published research papers. I have three tier-1 publications, including Internet of Things (Elsevier), Biomedical Signal Processing and Control (Elsevier), and IEEE Access. In my research journey, I have collaborated with NASA Glenn Research Center, Cleveland Clinic, and the U.S. Department of Energy for various research projects. I am also an official reviewer and have reviewed over 100 research papers for Elsevier, IEEE Transactions, ICRA, MDPI, and other top journals and conferences. I hold a PhD from Cleveland State University with a focus on large language models (LLMs) in cybersecurity, and I also earned a master’s degree in informatics from Northeastern University.
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Why LLM Hallucinations Aren’t Bugs

Watch: Why Large Language Models Hallucinate by IBM Technology LLM hallucinations aren’t bugs-they’re a byproduct of how these models are trained, evaluated, and incentivized to perform. Understanding this requires examining the interplay between statistical prediction, evaluation metrics, and the…
Thumbnail Image of Tutorial Why LLM Hallucinations Aren’t Bugs
Image of Author Dr. Dipen
Dr. Dipen
I am an AI/ML researcher with 150+ citations and 16 published research papers. I have three tier-1 publications, including Internet of Things (Elsevier), Biomedical Signal Processing and Control (Elsevier), and IEEE Access. In my research journey, I have collaborated with NASA Glenn Research Center, Cleveland Clinic, and the U.S. Department of Energy for various research projects. I am also an official reviewer and have reviewed over 100 research papers for Elsevier, IEEE Transactions, ICRA, MDPI, and other top journals and conferences. I hold a PhD from Cleveland State University with a focus on large language models (LLMs) in cybersecurity, and I also earned a master’s degree in informatics from Northeastern University.
•Last Updated:
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