Skip to main content
Liz

Liz

Follow your heart

LLM Summary

LLM Summary

    1. The Platform for LLM evals
    1. LLM Organization and Product
LizAbout 2 minLLMLLM
Llama Source Code Exploration

Llama Source Code Exploration

    1. About
    1. Llama Overall Architecture
    1. Hyperparameters
    1. Tensor Dimensionality Transformation
    1. Number of Trainable Parameters
    1. Source Code
LizAbout 5 minLLMLLM
Transformer Source Code Exploration

Transformer Source Code Exploration

    1. About
    1. Transformer Overall Architecture
    1. Hyperparameters
    1. Tensor Dimensionality Transformation
    1. Number of Trainable Parameters
    1. Source Code
LizAbout 16 minLLMLLM
Understanding LangChain in One Article: Building Powerful Applications with Large Language Models

Understanding LangChain in One Article: Building Powerful Applications with Large Language Models

Starting with the architecture diagram, step by step, this article helps you understand all aspects of LangChain.

    1. What is LangChain?
    1. What Information Does the LangChain Architecture Diagram Tell Us?
    1. Essential Core Modules You Need to Know
    1. Experience the Function of Each Module Through Simple Example Code
LizAbout 4 minLLMLLM
PyG Heterogeneous Graph Practice

PyG Heterogeneous Graph Practice

Homogeneous Graph and Heterogeneous Graph

Homogeneous graph

Without distinguishing between node and edge types, there is only one type of node and one type of edge.

Node Type + Edge Type = 2

For example, in a social network, it can be imagined that nodes only have one category 'person', and edges only have one type of connection 'knows'. And people either know each other or they do not.

LizLess than 1 minutePytorchPytorch
Building Conversational Applications with Streamlit

Building Conversational Applications with Streamlit

    1. Components Required for Constructing a Dialogue Interface
    1. Complete Process of Dialogue Interface
    1. Refactoring for Streaming Output of Assistant Messages
    1. Building an Application that Encapsulates ChatGPT
LizAbout 2 minLLMLLM
Deep Learning Practice with PyTorch

Deep Learning Practice with PyTorch

    1. PyTorch's APIs
    1. Data Loading and Preprocessing
    1. Defining Network Models
    1. Defining Loss Function and Optimizer
    1. Training the Network
    1. Testing the Network
    1. Saving and Loading Models
    1. GPU Acceleration
    1. Visualization with TensorBoard
LizAbout 9 minPytorchPytorch
Tensor Operations

Tensor Operations

    1. Scalar, Vector, Matrix, and Tensor
    1. Initializing Tensors
    1. Attributes of Tensors
    1. Basic Operations on Tensors
    1. Summation and Averaging
    1. Product Operations
    1. Calculating the Norm of a Vector
    1. Gradient Computation
LizAbout 10 minPytorchPytorch