twitter-roberta-base-emotion-multilabel-latest

Uso

tweetnlp

Instalar tweetnlp vía pip:

pip install tweetnlp

Cargar el modelo en Python:

import tweetnlp

model = tweetnlp.load_model('topic_classification', model_name='cardiffnlp/twitter-roberta-base-emotion-multilabel-latest')

model.predict("I bet everything will work out in the end :)")

Salida esperada:

{'label': ['joy', 'optimism']}

pipeline

Instalar Tensorflow:

pip install -U tensorflow==2.10

Uso con la biblioteca transformers:

from transformers import pipeline

pipe = pipeline("text-classification", model="cardiffnlp/twitter-roberta-base-emotion-multilabel-latest", return_all_scores=True)

pipe("I bet everything will work out in the end :)")

Salida esperada:

[[{'label': 'anger', 'score': 0.018903767690062523}, {'label': 'anticipation', 'score': 0.28172484040260315}, {'label': 'disgust', 'score': 0.011607927270233631}, {'label': 'fear', 'score': 0.036411102861166}, {'label': 'joy', 'score': 0.8812029361724854}, {'label': 'love', 'score': 0.09591569006443024}, {'label': 'optimism', 'score': 0.9810988306999207}, {'label': 'pessimism', 'score': 0.016823478043079376}, {'label': 'sadness', 'score': 0.01889917254447937}, {'label': 'surprise', 'score': 0.02702752873301506}, {'label': 'trust', 'score': 0.4155798852443695}]]