huggingface

A Bert2Bert model which able to generate headlines!

This application utilizes the powerful Florence-2 vision-language model from Microsoft to generate comprehensive captions for images. The model is capable of understanding visual content and expressing it in natural language.

In this end to end project I have built a RAG app using ObjectBox Vector Databse and LangChain. With Objectbox you can do OnDevice AI, without the data ever needing to leave the device.

The model is based on a YOLOv8 (Deep learning Neural network architecture) and is trained on the publicly available dataset, which consists of lung CT scans of patients with and without lung cancer.

Runtime detector for reward hacking and misalignment in LLM agents (89.7% F1 on 5,391 trajectories).

1st Prize for Creativity at Agents & MCP Hackathon 2025. Transform raw footage into viral-ready content in seconds. No skills required. No expensive gear needed. Just your vision and our AI.

A Classification Approach: Making LLM Knowledge-Aware

HFDownloader - Hugging Face Model Downloader

Fast and practical image deraining with PyTorch.

Build LLM-enabled FastAPI applications without build configuration.

Welcome to the Document QA system! This repository contains the code for a system that allows you to ask questions about your documents and get answers based on their contents. It supports a wide range of document formats, including PDF, Word, Excel, PowerPoint, text files, and even images!

⚡ LLaMA-2 model experiment

Fine-Tuned Language Models Exploration using LoRA and Hugging Face's Transformers Library

GenAI - Building AI Workflows | Agentic Appls | Working with LLMs | HuggingFace | OpenAI | Gemini

FastText Pytorch version

This is a repository about Text Summarization

Local AI model manager

Realism Adapter for Flux.1 Dev

Comparing Selective Masking Methods for Depression Detection in Social Media

[ACL 2026 Oral] Official code, UIQ benchmark, and pretrained checkpoints for "Omni-Embed-Audio: Leveraging Multimodal LLMs for Robust Audio-Text Retrieval" (Yoo et al., Sogang University)