How to Use DeepScaleR-1.5B-Preview with Hugging Face Inference Endpoints: A Step-by-Step Tutorial

If you’re excited about DeepScaleR-1.5B-Preview, the compact yet powerful language model that outperforms OpenAI’s o1-preview, you’re in the right place! In this tutorial, I’ll walk you through how to use this model with Hugging Face Inference Endpoints. Whether you’re a developer, researcher, or AI enthusiast, this guide will help you get started in minutes.

What You’ll Need

1. A Hugging Face account (sign up here if you don’t have one).
2. An API key from Hugging Face (you can generate one in your account settings).
3. Basic knowledge of Python.

Step 1: Install the Required Library

To interact with Hugging Face Inference Endpoints, you’ll need the huggingface_hub library. If you don’t have it installed, run the following command:

pip install huggingface_hub

Step 2: Set Up the Inference Client

Once the library is installed, you can set up the InferenceClient to interact with the DeepScaleR-1.5B-Preview model. Here’s the code to get started:

from huggingface_hub import InferenceClient

# Initialize the InferenceClient
client = InferenceClient(
    provider="hf-inference",
    api_key="api_key"  # Replace with your Hugging Face API key
)