language models

Power in Action: Elevating Input Prompts with Verb-Centric Precision

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Unleashing the Potential: Elevating Input Prompts with Verb-Centric Precision Introduction: Greetings, prompt engineering enthusiasts! As we journey through the fascinating landscape of prompt engineering, we arrive at the twelfth methodology: “Using Verbs to Enhance Input Prompts.” In our previous explorations, we’ve dived into sentiment analysis, text transformation, expert personas, and more. Today, we unravel the … Read more

OpenAI Files Trademark Application for GPT-5

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OpenAI Files Trademark Application for GPT-5: A Milestone in AI Advancements OpenAI, a non-profit research company, has filed a trademark application for GPT-5, the next generation of its large language model. The trademark application covers a wide range of software related to language models and AI, including downloadable computer programs, artificial production of human speech … Read more

[LangChain] API Reference

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How to interact with LangChain programmatically using the API reference The LangChain API reference provides a comprehensive overview of all the methods available for interacting with LangChain programmatically. The API reference is divided into the following sections: The different methods available for loading models, generating text, translating languages, and answering questions The API reference provides … Read more

[NLP with Transformers] Text Preprocessing for NLP

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Tokenization and Subword Encoding: Output: Handling Special Tokens and Padding: Output: Data Cleaning and Normalization Techniques: Output: These sample codes show how to use HuggingFace’s Tokenizers library and regular expressions to accomplish tokenization, subword encoding, managing special tokens and padding, as well as data cleaning and normalization procedures. Based on your unique NLP goals and … Read more

[NLP with Transformers] Fundamentals of Transformers

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Understanding the Transformer Architecture: Self-Attention Mechanism: Transformer Layers and Multi-Head Attention: Positional Encoding: Sample Code Example (using Python and PyTorch): This example program uses PyTorch to demonstrate a condensed version of a Transformer model. It comprises the key elements covered, including positional encoding, the Transformer layer, and multi-head attention. Keep in mind that there are … Read more

[NLP with Transformers] Introduction to Natural Language Processing

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Introduction to Natural Language Processing An overview of natural language processing (NLP) and its uses will be given in this section. We will also go over some fundamental ideas and terms that are used in the industry. We’ll also provide sample code to get you started using Transformers for NLP. Overview of NLP: A branch … Read more