TimeGPT SDK
Project description
Nixtla
NixtlaTS
Forecast using TimeGPT
NixtlaTS offers a collection of classes and methods to interact with the API of TimeGPT.
🕰️ 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:
pip install nixtlats>=0.1.0
🎈 Quick Start
Get started with TimeGPT now:
df = pd.read_csv('https://raw.githubusercontent.com/Nixtla/transfer-learning-time-series/main/datasets/electricity-short.csv')
from nixtlats import TimeGPT
timegpt = TimeGPT(
# defaults to os.environ.get("TIMEGPT_TOKEN")
token = 'my_token_provided_by_nixtla'
)
fcst_df = timegpt.forecast(df, h=24, level=[80, 90])
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