This Jupyter Notebook (huggingface.ipynb) demonstrates how to use the Hugging Face transformers library for text generation, summarization, or other NLP tasks.

Prerequisites Ensure you have the following installed:

• Python 3.7+
• transformers library
• torch (if using PyTorch models)
• requests (for API calls)

To install dependencies, run:

pip install transformers torch requests

Setup

1. Get Your Hugging Face API Key

• Sign up at Hugging Face
• Navigate to Settings > Access Tokens
• Create an API token

2. Set Up Your API Key Set your API key as an environment variable:

 Windows
set HF_API_KEY=your_api_key

 macOS/Linux
export HF_API_KEY=your_api_key

Usage Running the Notebook

1. Open Jupyter Notebook:

   jupyter notebook

2. Load huggingface.ipynb and execute the cells step by step.

Features

• Text generation using Hugging Face models
• API-based and local model inference
• Error handling and logging

Customization

• Modify the prompt in the notebook to fit your use case.
• Change the model used by updating the model_name variable.