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my_llm_researchhub's Introduction

My LLM Research Hub ๐Ÿš€

Welcome to the My LLM Research Hub! ๐Ÿ“š This repository is a hub for tech enthusiasts diving into the fascinating world of Language Models (LLMs), especially focusing on transformer models and their innovative applications in NLP tasks. Here, we blend cutting-edge AI research with a dash of humor to make learning both informative and fun! ๐Ÿค–๐Ÿ’ฌ

Table of Contents

Code Examples

Dive into our code examples where we explore various aspects of LLMs and transformers. Each notebook is a journey through the capabilities of these models, showcasing practical implementations and experiments.

Base Examples of Using Transformers

  • Sentimental Analysis with Transformers: Explore the core functionalities of transformer models in sentiment analysis. This notebook is a great starting point for understanding how transformers process text data to determine sentiment.
  • Sentimental Analysis Machine Learning: A dive into machine learning approaches for sentiment analysis, contrasting traditional methods with transformer-based techniques.

Hugging Face Models

  • Sentiment Analysis with Hugging Face: Utilize the Hugging Face library for quick and efficient sentiment analysis. This notebook demonstrates the power and ease of using pre-trained models for complex NLP tasks.
  • Chatbot Implementation: Step into the world of conversational AI by building a chatbot using Hugging Face's transformers. A fun and interactive way to understand dialogue systems.
  • Falcon Chatbot: Advanced chatbot development using the Falcon framework, showcasing how to integrate transformer models into web applications for real-time interactions.

LLM Specific Code

  • RAG Notebook: Delve into Retrieval Augmented Generation (RAG) and its applications in enhancing language model outputs with external knowledge sources.
  • Langchain Retrieval: Investigate advanced retrieval techniques in language models, focusing on chaining multiple models for complex query answering.
  • Llama Index: Explore indexing methods tailored for LLMs, crucial for efficient information retrieval and data organization.

Research Papers

Evaluation Papers

  • ๐Ÿ“„ Bert Semantic Evaluation: A deep dive into the semantic evaluation of BERT models, essential reading for understanding model performance and limitations.
  • ๐Ÿ“„ Blue Ngram Evaluation: Explore the intricacies of n-gram based evaluation metrics in NLP, a cornerstone for assessing language model outputs.

RAG Papers

  • ๐Ÿ“„ REALM Paper: Delve into the REALM of knowledge-augmented language models and their transformative impact on NLP tasks.
  • ๐Ÿ“„ RAG for NLP Tasks: Understand how Retrieval Augmented Generation is revolutionizing various NLP tasks, from question answering to content generation.
  • ๐Ÿ“„ Transformer Paper: A comprehensive look at the transformer architecture, the backbone of modern NLP.

Presentation Materials

License

This project is licensed under the MIT License.

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