Tools made for usage alongside artistic style transfer projects

RAFT, or Retrieval-Augmented Fine-Tuning, is a method comprising of a fine-tuning and a RAG-based retrieval phase. It is particularly suited for the creation of agents that realistically emulate a specific human target.

🧹 Gracefully shutdown Node.js application: help you handle exit signals and cleanup

Developed a sophisticated machine learning model capable of generating diverse interview questions aligned with specific topics, ensuring depth of conversation. Integrated advanced Natural Language Processing (NLP) algorithms to analyse spoken responses, identifying grammatical errors & offering accurate corrections after the interview.

Fyne Thyngges provided by Learning Objects, for Use with ScalaZ and Libraries of a similar Nature and Quality.

Natural Language Processing (NLP) and Large Language Models (LLM) with Fine-Tuning LLM and make Chatbot Question answering (QA) with LoRA and Flan-T5 Large

For conceptual understanding you can refer my medium blog which will provide you in-depth knowledge of SVC along with various other factors required in data science.

A fine-tuned version of Phi-3-mini-4k-instruct for generating SQL queries from natural language prompts, utilizing synthetic datasets and QLoRA for efficient adaptation and deployment.

Fine grained sentiment analysis on App Reviews with deep learning.

Forecasting Energy Consumption with XGBOOST and Optuna Optimizer

Finite Element Methods Labolatories

This project is designed to classify YouTube comments as toxic or non-toxic using BERT (Bidirectional Encoder Representations from Transformers). By fine-tuning a pre-trained BERT model, we leverage state-of-the-art NLP capabilities to identify harmful content in online conversations.

Fine Set is a collection of unique elements maintained as linked list. It uses fine grained locks, allowing pipelined traversal by threads.

A simple site to display activity in my art studio.

PyDownloader is a new python script app to download requirement and enjoy the python!

Development of a Traffic Speed control record application.