Huggingface

DS_Portfolio/HuggingFace.ipynb at main · gauravry/DS_Portfolio (github.com) 

Hugging Face is a platform and an open-source library called Transformers, which facilitates Natural Language Processing (NLP) tasks using state-of-the-art pre-trained models. Here's how it works:

1. Model Repository: Hugging Face provides a repository of pre-trained NLP models. These models are trained on large datasets and are capable of performing various NLP tasks like text classification, named entity recognition, question answering, text generation, and more.

2. Transformers Library: The Transformers library is the core component of Hugging Face's ecosystem. It allows users to easily load, fine-tune, and utilize these pre-trained models. The library is compatible with popular deep learning frameworks like PyTorch and TensorFlow.

3. Tokenization: Tokenization is the process of converting raw text into numerical tokens that the model can understand. Hugging Face's library includes tokenizers for different models, which split text into tokens and convert them into input suitable for the models.

https://colab.research.google.com/drive/1tBoBgO66REGNxqzI3C4EFUky54UY4EyJ?usp=sharing