Uncover deeper insights from your reviews! This project delves into the potential of Large Language Models (LLMs) to extract granular sentiment insights from reviews.
By leveraging LLaMA2, fine-tuned with Ludwig and Langchain, and employing advanced prompt engineering and vector database, we aim to significantly enhance conventional sentiment analysis methods in accurately classifying sentiments towards specific product or service aspects.
My Contribution
I played a crucial role in enhancing the model's performance by meticulously fine-tuning the LLaMA2 model. My expertise in data preprocessing ensured optimal data quality for training.
Additionally, I optimized the model's architecture and parameters to achieve superior accuracy and efficiency in sentiment analysis.
Tech Stack
JavaScript
TypeScript
Llama 2
MongoDB
PostgreSQL
ReactJS
REST
LlamaIndex
LangChain
Ludwig
Tailwind CSS
Prisma ORM
Role
Machine Learning Engineer
Company
Personal
Timeline
Sep 2023 - Oct 2023
Developers
Repositories
Images
