Text Classification
Transformers
PyTorch
Spanish
roberta
sagemaker
ruperta
TextClassification
SentimentAnalysis
text-embeddings-inference
Instructions to use edumunozsala/RuPERTa_base_sentiment_analysis_es with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use edumunozsala/RuPERTa_base_sentiment_analysis_es with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="edumunozsala/RuPERTa_base_sentiment_analysis_es")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("edumunozsala/RuPERTa_base_sentiment_analysis_es") model = AutoModelForSequenceClassification.from_pretrained("edumunozsala/RuPERTa_base_sentiment_analysis_es") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 18c9e484c2e06fe2b9988499f374ea2bb9148f6978c021a5fad283e6cdb9a2c3
- Size of remote file:
- 2.42 kB
- SHA256:
- d3e2df9d5019e15fd17f73664ef9fabbf698f2c0068074c59f34b7383659bdbd
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