🤖 Large Language Models (LLMs)
This repo is dedicated to learning and working with large language models (LLMs), prompt engineering, and modern GenAI tools such as LangChain, RAG, and vector databases.
Overview
what is LLMs?
LLMs is a repository dedicated to learning and working with large language models (LLMs), prompt engineering, and modern GenAI tools such as LangChain, RAG, and vector databases.
how to use LLMs?
To use LLMs, explore the folder structure for various topics, including transformers, prompt engineering, and LangChain pipelines. You can clone the repository and follow the provided examples to get started.
key features of LLMs?
- Comprehensive resources on transformer architecture and pretraining vs finetuning.
- Strategies for effective prompt engineering, including few-shot prompting and instruction tuning.
- Implementation of LangChain pipelines and RAG systems for advanced applications.
use cases of LLMs?
- Developing applications that utilize large language models for natural language processing tasks.
- Experimenting with prompt engineering techniques to improve model responses.
- Building systems that integrate memory and vector stores for enhanced AI capabilities.
FAQ from LLMs?
- What are large language models?
Large language models are AI models trained on vast amounts of text data to understand and generate human-like text.
- How can I contribute to the LLMs project?
You can contribute by submitting issues, pull requests, or suggestions on GitHub.
- Is there documentation available?
Yes, the repository includes documentation and examples to help you get started.
Project Info
Created At
a year agoUpdated At
a year agoAuthor Name
RahulSaini02Star
0Language
-License
-Category
research-and-data
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