Hugging Face

Transfer Learning for Text Classification Using Hugging Face Transformers Trainer Fine-tuning a pretrained transformer BERT model for customized sentiment analysis using transformer PyTorch Trainer from Hugging Face

Transfer Learning for Text Classification Using Hugging Face Transformers Trainer

Hugging Face provides three ways to fine-tune a pretrained text classification model: Tensorflow Keras, PyTorch, and transformer trainer. Transformer trainer is an API for feature-complete training in PyTorch without writing all the loops. This tutorial will use the transformer trainer to fine-tune a text classification model. We will talk about the following: Resources for this …

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Customized Sentiment Analysis: Transfer Learning Using Tensorflow with Hugging Face Fine-tune a pretrained transformer model for customized sentiment analysis using TensorFlow Keras with Hugging Face

Customized Sentiment Analysis: Transfer Learning Using Tensorflow with Hugging Face

Transfer learning is also called pretrained model fine-tuning. It refers to training a model with a small dataset while leveraging the stored information from a model trained with a large dataset for another task. In this tutorial, we will talk about how to use a small review dataset to build a sentiment prediction model while …

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Sentiment Analysis: Hugging Face Zero-shot Model vs Flair Pre-trained Model Which pre-trained Natual Language Processing (NLP) model has better prediction accuracy for the sentiment analysis, Hugging Face or Flair?

Sentiment Analysis: Hugging Face Zero-shot Model vs Flair Pre-trained Model

There are different methods for sentiment analysis. Some examples are lexicon-based methods, building customized models, using cloud services for sentiment predictions, or using pre-trained language models. In this tutorial, we will compare two state-of-art deep-learning pre-trained models for sentiment analysis, one from Hugging Face, and the other from Flair. We will talk about: Resources for …

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