Metadata-Version: 2.1
Name: pysentimiento
Version: 0.0.1.2
Summary: A Transformer-based library for Sentiment Analysis in Spanish
Home-page: https://github.com/finiteautomata/pysentimiento
Author: Juan Manuel Pérez, Juan Carlos Giudici, Franco Luque
Author-email: jmperez@dc.uba.ar
License: UNKNOWN
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](https://colab.research.google.com/assets/colab-badge.svg)](https://colab.research.google.com/drive/1ItS0-ZPXGcEeVmRmHaneX3w8eq6Vhdde?usp=sharing)
        
        ```python
        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`](https://github.com/huggingface/transformers) library.
        
        ```python
        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
        
        - [`beto-sentiment-analysis`](https://huggingface.co/finiteautomata/beto-sentiment-analysis)
        
        ## Instructions for developers
        
        1. First, download TASS 2020 data to `data/tass2020` (you have to register [here](http://tass.sepln.org/2020/?page_id=74) to download the dataset)
        
        Labels must be placed under `data/tass2020/test1.1/labels`
        
        2. Run script to train models
        
        ```
        python bin/train.py "dccuchile/bert-base-spanish-wwm-cased" models/beto-sentiment-analysis/ --epochs 3
        ```
        
        3. 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](https://github.com/finiteautomata/pysentimiento/issues) to point out bugs and make suggestions (new models, use another datasets, some other languages, etc)
        
Platform: UNKNOWN
Classifier: Programming Language :: Python :: 3
Classifier: License :: OSI Approved :: MIT License
Classifier: Operating System :: OS Independent
Requires-Python: >=3.6
Description-Content-Type: text/markdown
