shorif-crypto-trend-lite

Overview

shorif-crypto-trend-lite is a lightweight regression model designed to predict short-term cryptocurrency price movement trends based on historical numerical indicators.

Model Architecture

The model uses a simplified transformer-inspired feed-forward architecture optimized for time-series regression.

Intended Use

• Educational crypto trend analysis
• Research and simulation
• Non-financial advisory experiments

Limitations

• Not a financial advice system
• Sensitive to noisy or incomplete data
• Not suitable for long-term forecasting

Example Code

import torch
model = torch.load("shorif-crypto-trend-lite.pt")
prediction = model(torch.randn(1, 12))