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BETO(cased)
This model was built using pytorch.
Model description
Input for the model: Any spanish text Output for the model: Sentiment. (0 - Negative, 1 - Positive(i.e. technology relate))
How to use
Here is how to use this model to get the features of a given text in PyTorch:
# You can include sample code which will be formatted
from transformers import AutoTokenizer, AutoModelForSequenceClassification
tokenizer = AutoTokenizer.from_pretrained("hiiamsid/BETO_es_binary_classification")
model = AutoModelForSequenceClassification.from_pretrained("hiiamsid/BETO_es_binary_classification")
text = "Replace me by any text you'd like."
encoded_input = tokenizer(text, return_tensors='pt')
output = model(**encoded_input)
Training procedure
I trained on the dataset on the dccuchile/bert-base-spanish-wwm-cased.
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