---
language:
  - en
license: apache-2.0
tags:
  - time-series
  - anomaly-detection
  - transformer
  - explainability
pipeline_tag: time-series-forecasting
library_name: pytorch
base_model: custom
---

# 🧠 CHRONOGUARD: Temporal Anomaly Detection & Forecasting Model

**CHRONOGUARD** is an advanced hybrid deep learning model for **time-series anomaly detection**, **trend forecasting**, and **temporal risk visualization**.  
It combines **Temporal Convolutional Networks (TCN)**, **Bidirectional LSTMs**, and **Attention Mechanisms** to learn both short-term fluctuations and long-term dependencies from sequential data.

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## 🚀 Features

- 🧩 **Multimodal Input Support** — numeric, categorical, and contextual data  
- 🔍 **Attention-based Anomaly Detection** — identifies irregular temporal patterns in real time  
- 📈 **Forecast Generation** — predicts next-step or multi-step sequences  
- 🧠 **Explainability via Heatmaps** — attention and saliency visualizations for model interpretability  
- 💾 **Lightweight, Scalable Architecture** — works on CPU/GPU and deploys easily to Hugging Face Spaces or Streamlit

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