| # Sentiment analysis model | |
| <!-- Provide a quick summary of what the model is/does. --> | |
| This model aims to demonstrate text classification task through sentiment analysis | |
| ### Model Description | |
| <!-- Provide a longer summary of what this model is. --> | |
| - **Developed by:** [Nilton Seixas] | |
| - **Language(s) (NLP):** [English] | |
| - **License:** [More Information Needed] | |
| - **Finetuned from model [optional]:** [distilbert-base-cased] | |
| ### Model Sources [optional] | |
| <!-- Provide the basic links for the model. --> | |
| - **Repository:** [niltonseixas/sentiment_analysis] | |
| - **Paper [optional]:** [More Information Needed] | |
| - **Demo [optional]:** [More Information Needed] | |
| ## Uses | |
| <!-- Address questions around how the model is intended to be used, including the foreseeable users of the model and those affected by the model. --> | |
| from transformers import AutoTokenizer, AutoModelForTokenClassification | |
| from transformers import pipeline | |
| tokenizer = AutoTokenizer.from_pretrained("niltonseixas/sentiment_analysis_tokenizer") | |
| model = pipeline("text-classification", model="niltonseixas/sentiment_analysis", tokenizer=tokenizer) | |
| model("I'm in love with NLP") |