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:
- dce392197304b74ed3ef7e1827cb4b22746ee3e38ea7aac8d75499537fa415d7
- Size of remote file:
- 504 MB
- SHA256:
- 41ce4881fd31109522c4ab5fe9495c902eeaa6f9f5905aff32734d20661ce9cc
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