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<div align="center">
<img src="https://raw.githubusercontent.com/Nixtla/neuralforecast/main/nbs/imgs_indx/logo_mid.png">
<h1 align="center">NixtlaTS</h1>
<h3 align="center">Forecast using TimeGPT</h3>
    
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**NixtlaTS** offers a collection of classes and methods to interact with the API of TimeGPT.
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Certainly, adding a bit of personality and visual appeal can make your README stand out. Here's a reworked version:

---

# 🕰️ TimeGPT: Revolutionizing Time-Series Analysis

Developed by Nixtla, TimeGPT is a cutting-edge generative pre-trained transformer model dedicated to prediction tasks. 🚀 By leveraging the most extensive dataset ever – financial, weather, energy, and sales data – TimeGPT brings unparalleled time-series analysis right to your terminal! 👩‍💻👨‍💻

In seconds, TimeGPT can discern complex patterns and predict future data points, transforming the landscape of data science and predictive analytics.

## ⚙️ Fine-Tuning: For Precision Prediction

In addition to its core capabilities, TimeGPT supports fine-tuning, enhancing its specialization for specific prediction tasks. 🎯 This feature is like training a machine learning model on a targeted data subset to improve its task-specific performance, making TimeGPT an even more versatile tool for your predictive needs.

## 🔄 `NixtlaTS`: Your Gateway to TimeGPT

With `NixtlaTS`, you can easily interact with TimeGPT through simple API calls, making the power of TimeGPT readily accessible in your projects.

## 💻 Installation

Get `NixtlaTS` up and running with a simple pip command:

```python
pip install nixtlats>=0.1.0
```

## 🎈 Quick Start

Get started with TimeGPT now:

```python
from nixtlats import TimeGPT
timegpt = TimeGPT(token=os.environ['TIMEGPT_TOKEN'])
fcst_df = timegpt.forecast(df, h=24, freq='H', level=[80, 90])
```

![](./nbs/img/forecast_readme.png)
