Welcome to the My LLM Research Hub! ๐ 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! ๐ค๐ฌ
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.
- 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.
- 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.
- 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.
- ๐ Bert Semantic Evaluation: A deep dive into the semantic evaluation of BERT models, essential reading for understanding model performance and limitations.
- ๐ Blue Ngram Evaluation: Explore the intricacies of n-gram based evaluation metrics in NLP, a cornerstone for assessing language model outputs.
- ๐ REALM Paper: Delve into the REALM of knowledge-augmented language models and their transformative impact on NLP tasks.
- ๐ RAG for NLP Tasks: Understand how Retrieval Augmented Generation is revolutionizing various NLP tasks, from question answering to content generation.
- ๐ Transformer Paper: A comprehensive look at the transformer architecture, the backbone of modern NLP.
- ๐ฅ Retrieval Augmented Generation Presentation: A visually engaging presentation that breaks down the concepts of RAG for easy understanding.
This project is licensed under the MIT License.