Data and code for FreshLLMs (https://arxiv.org/abs/2310.03214)
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Updated
Nov 24, 2025 - Jupyter Notebook
Data and code for FreshLLMs (https://arxiv.org/abs/2310.03214)
The course provides guidance on best practices for prompting and building applications with the powerful open commercial license models of Llama 2.
Python Project Sample for Demonstration
pyWhat LLM version | Answer "What is it?" on the command line with the power of large language models
Dynamic Few-Shot Prompting is a Python package that dynamically selects N samples that are contextually close to the user's task or query from a knowledge base (similar to RAG) to include in the prompt.
Leveraged the power of Google Cloud's Vertex AI platform to develop advanced Large Language Models (LLMs). Utilizing the Python API provided by Google Cloud, this endeavor represents a significant stride in the realm of natural language processing and LLMs.
This project implements a text classification system powered by Large Language Models (LLMs) running locally. The goal is to leverage the capabilities of modern LLMs to automatically categorize and label text data without relying on external APIs or manual human labeling, ensuring privacy, autonomy, and efficiency in text processing tasks.
repo for "An Adapted Few-Shot Prompting Technique Using ChatGPT to Advance Low-Resource Languages Understanding" (2025)
Prompt Design & LLM Judge
The study explores zero-shot and few-shot prompting strategies using Meta's quantized LLaMA 3.1 70B model to perform Named Entity Recognition (NER) on Nepali text.
📊 Analyze real-world data on Data Science job salaries, benchmarking prediction performance using multiple approaches: traditional ML models, few-shot prompting, and fine-tuned LLMs.
Dynamic Few-Shot Prompting for Customer Support AI Agents A practical implementation of dynamic few-shot prompting using LangChain and HuggingFace models. This repository provides an optimized approach to improving AI agent performance for customer support tasks by selecting relevant examples based on user queries, thus enhancing response accuracy
Prompt Design & LLM Judge
[EMNLP 2025] COM-BOM: Bayesian Exemplar Search for Efficiently Exploring the Accuracy-Calibration Pareto Frontier
An educational chatbot that employs the Feynman technique—acting as a student and forcing the user to teach a study topic, thereby exposing gaps in the user's understanding.
Unlocking the Power of Generative AI: In-Context Learning, Instruction Fine-Tuning, Reinforcement Learning Fine-Tuning, Retrieval Augmented Generation and LangGraph Workflows for AI Agents.
Solution Hacks 2025 Winner. An educational chatbot that employs the Feynman technique—acting as a student and forcing the user to teach a study topic, thereby exposing gaps in the user's understanding. This repo hosts the AI Model to support the Feynomenon app.
This repository contains results from my MSc. thesis on "Test Case Generation from User Stories using Generative AI Techniques with LLM Models." Each folder includes generated test cases in PDF, detailed metrics scores of data in Excel sheets, and visual graphs, offering a comprehensive view of the experiments in images folder and their outcomes.
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