The notebook focuses on text generation or sentiment analysis using natural language processing (NLP) techniques. It utilises pre-trained models from the Hugging Face library, such as GPT-2, to work with text data.
Approach
Text Processing:
- Loading, cleaning, and preparing text data.
- Exploratory data analysis (EDA)
Model Usage:
- Uses a pre-trained language model, Hugging Face. The model is used for tasks such as text generation or predicting sentiment.
- The default model (openai-community/gpt2) was used for text generation without specifying a model name.
Example Outputs:
- The notebook includes examples of text generation, where an initial phrase is extended by the model.
- Example: "In this course, I will teach you how to…" was extended with generated content related to building WordPress sites.
Analysis Type
- Text Generation: Extending given text using a language model.
- Sentiment Analysis: Predicting the sentiment of text data (positive, negative, or neutral).
Execution
- Loaded a pre-trained model
- Text Generation
- Pipeline Execution