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Fine-tuning-an-LLM-using-LoRA
π Text Classification with LoRA (Low-Rank Adaptation) of Language Models - Efficiently fine-tune large language models for text classification tasks using the Stanford Sentiment Treebank (SST-2) dataset and the LoRA technique.LungTumor-Segmentation
Automatically segment lung cancer in CTsChat-Bot-using-Streamlit-and-OpenAI
This repository hosts a user-friendly chatbot application, powered by the GPT-3.5 model and built with the Streamlit framework. Engage in dynamic conversations, ask questions, and enjoy interactive responses with ease. Customize and extend its capabilities to suit your specific requirements.3D-Liver-Segmentation
Automatically segment the liver and liver tumors in CT scans with 3D-UNETImage2AudioStoryConverter
Convert images into captivating audio stories using image-to-text, language models, and text-to-speech technologies. Upload images, generate stories, and listen to the narrated audio clips. A fun project combining AI and creativity.FaceEmotionRecognition
Build a Face Emotion Recognition (FER) AlgorithmAtrium-Segmentation
Automatically segment the left Atrium in cardiac imagesSimilar-Paper-Reccomendation
This repository contains an application designed to recommend scientific papers that are most similar to a given input paragraph. The application uses the llama and weaviate libraries to achieve this.Pneumonia-Classification
Identify size of pneumonia in X-Ray imagesCardiac-Detection
Predict a bounding box around the heart in X-ray images.train_scheduling_assistant
This project utilizes a fine-tuned Large Language Model (LLM) to generate train scheduling information from unstructured textual data, providing an interactive UI via Streamlit.Machine-Learning-App-Deployment-on-Amazon-EKS-with-MLOps-Practices
This repository demonstrates the deployment of a machine learning app on Amazon EKS using Docker and Kubernetes, with the incorporation of MLOps practices such as version control, CI/CD, and infrastructure as code.ReAct-Framework-Implementation
This repository implements the "ReAct" framework, combining OpenAI's GPT-3.5 Turbo model and LangChain for dynamic reasoning and interaction with external data sources.SkinLesionSegmentation
SkinLesionSegmentation is a Python project that focuses on segmenting and visualizing skin lesions in images using computer vision techniques. Skin lesions can carry crucial diagnostic information in the field of dermatology, and this project aims to provide a tool for extracting and analyzing these lesions.Skin-Lesion-Classification-App
This repository contains the code for a machine learning application that classifies skin lesions as either Benign or Melanoma using a fine-tuned DenseNet121 model. The model has been trained on the HAM10000 dataset and deployed as a web application using Streamlit.DeepLabV3-with-Squeeze-and-Excitation-Blocks-for-LIVECell-Dataset
This repository contains the implementation and deployment of a modified DeepLabV3 segmentation model with Squeeze-and-Excitation (SE) blocks trained on the LIVECell dataset.Love Open Source and this site? Check out how you can help us