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A Transformer-based library for Sentiment Analysis in Spanish

Project description

PySentimiento: Sentiment Analysis in Spanish

A simple Transformer-based library for Sentiment Analysis in Spanish (some other languages coming soon!).

Just do pip install pysentimiento and start using it:

Test it in Colab

from pysentimiento import SentimentAnalyzer
analyzer = SentimentAnalyzer()
analyzer.predict("Qué gran jugador es Messi")
# returns 'POS'
analyzer.predict("Esto es pésimo")
# returns 'NEG'
analyzer.predict("Qué es esto?")
# returns 'NEU'

analyzer.predict_probas("Dónde estamos?")
# returns {'NEG': 0.10235335677862167,
# 'NEU': 0.8503277897834778,
# 'POS': 0.04731876030564308}

Also, you might use pretrained models directly with transformers library.

from transformers import AutoTokenizer, AutoModelForSequenceClassification

tokenizer = AutoTokenizer.from_pretrained("finiteautomata/beto-sentiment-analysis")

model = AutoModelForSequenceClassification.from_pretrained("finiteautomata/beto-sentiment-analysis")

Trained models so far

Instructions for developers

  1. First, download TASS 2020 data to data/tass2020 (you have to register here to download the dataset)

Labels must be placed under data/tass2020/test1.1/labels

  1. Run script to train models
python bin/train.py "dccuchile/bert-base-spanish-wwm-cased" models/beto-sentiment-analysis/ --epochs 3
  1. Upload models to Huggingface's Model Hub

TODO:

  • Upload some other models
  • Train in other languages
  • Write brief paper with description

Suggestions and bugfixes

Please use the repository issue tracker to point out bugs and make suggestions (new models, use another datasets, some other languages, etc)

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