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Hi, Yuyang here. After learning from excellent people, I want to share my thoughts and experiences with you to contribute a little to the community. I hope you can find something useful here. HAPPY LEARNING😁😁!!!

LLM Part3: Applications

Overview
Large Language Model

In this blog, I am going to summary the 5 most common generative models: Auto-Regreesive Model, Variational AutoEncoder, Engery Based Model, Flow Model and Diffusion Model. I will also display the pros and cons between different models, and how we can combine those models to get better performance

1 min
70 words
2025-08-07

LLM Overview

Large Language Model
Overview

In this blog, I am going to summary the 5 most common generative models: Auto-Regreesive Model, Variational AutoEncoder, Engery Based Model, Flow Model and Diffusion Model. I will also display the pros and cons between different models, and how we can combine those models to get better performance

3 min
564 words
2025-08-07

LLM Part1: Pre Training

Overview
Large Language Model

In this blog, I am going to summary the 5 most common generative models: Auto-Regreesive Model, Variational AutoEncoder, Engery Based Model, Flow Model and Diffusion Model. I will also display the pros and cons between different models, and how we can combine those models to get better performance

3 min
419 words
2025-08-07

LLM: RAG

Large Language Model
Overview

In this blog, I am going to summary the 5 most common generative models: Auto-Regreesive Model, Variational AutoEncoder, Engery Based Model, Flow Model and Diffusion Model. I will also display the pros and cons between different models, and how we can combine those models to get better performance

5 min
965 words
2025-08-07

LLM Part2: Post Training

Overview
Large Language Model

In this blog, I am going to summary the 5 most common generative models: Auto-Regreesive Model, Variational AutoEncoder, Engery Based Model, Flow Model and Diffusion Model. I will also display the pros and cons between different models, and how we can combine those models to get better performance

1 min
1 words
2025-08-07

Speed Up Training for Neural Networks

Training Tricks

Training large neural networks can be time-consuming and resource-intensive. This blog post explores various techniques to speed up the training process, including optimizing calculating in the single GPUs, and parallelizing the training across multiple GPUs.

Yuyang Zhang
14 min
2,648 words
2025-08-07
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