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Small Language Model
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Oct 5, 20242 min read
What is a Small Language Model
Small language models (SLMs) are compact versions of large language models (LLMs), designed to perform specific natural language...


Oct 5, 20242 min read
Model Architecture
Small Language Models (SLMs) are characterized by their compact neural network architectures, which typically consist of fewer layers,...


Oct 5, 20243 min read
Learning Rate and Other Hyperparameters
Hyperparameters are settings that govern the training process and model architecture, significantly influencing performance, convergence,...


Oct 5, 20242 min read
Data Collection
Importance of High-Quality Data for SLMs SLMs are designed to perform well on specific tasks with limited computational resources. Unlike...


Oct 5, 20242 min read
Data Cleaning
Data cleaning, also known as data cleansing or data scrubbing, involves identifying and correcting errors, inconsistencies, and...


Oct 5, 20242 min read
Tokenization
What is Tokenization? Tokenization is the process of breaking down unstructured text into smaller units called tokens. These tokens can...


Oct 5, 20242 min read
Model Initialization
Model initialization is a crucial step in training small language models (SLMs), as it significantly impacts their performance and...


Oct 5, 20242 min read
Forward and Backward Passes
The forward and backward passes are fundamental components of the training process for small language models (SLMs). They involve the...


Oct 5, 20243 min read
Cost-optimization of Computational Resources
Cost optimization in training Small Language Models (SLMs) involves strategic decisions across various stages of the machine learning...


Oct 5, 20242 min read
Validation
Validation Data Set The validation data set is a crucial component in the training of Small Language Models (SLMs). It is used to...


Oct 5, 20242 min read
Adjustments
Purpose of Adjustment The Adjustment step aims to enhance the model's accuracy and reliability by addressing any discrepancies identified...


Oct 5, 20242 min read
Error Handling
Error handling in the training of Small Language Models (SLMs) is a critical aspect that ensures the models produce reliable and accurate...
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