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Data Collection

Importance of High-Quality Data for SLMs SLMs are designed to perform well on specific tasks with limited computational resources. Unlike...

Data Cleaning

Data cleaning, also known as data cleansing or data scrubbing, involves identifying and correcting errors, inconsistencies, and...

Oct 52 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...

Editorial Staff

Oct 5

Tokenization

What is Tokenization? Tokenization is the process of breaking down unstructured text into smaller units called tokens. These tokens can...

Editorial Staff

Oct 5

Performance Monitoring

Performance monitoring in the training of Small Language Models (SLMs) is essential for ensuring that these models meet their intended...

Editorial Staff

Oct 5

Model Fine-Tuning

Model fine-tuning in the training of Small Language Models (SLMs) is a crucial process that enhances the model's performance on specific...

Oct 52 min read

Model Initialization

Model initialization is a crucial step in training small language models (SLMs), as it significantly impacts their performance and...

Oct 52 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 52 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...