Text Classification
Transformers
PyTorch
Safetensors
Spanish
roberta
sagemaker
roberta-bne
TextClassification
SentimentAnalysis
Eval Results (legacy)
text-embeddings-inference
Instructions to use edumunozsala/roberta_bne_sentiment_analysis_es with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use edumunozsala/roberta_bne_sentiment_analysis_es with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="edumunozsala/roberta_bne_sentiment_analysis_es")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("edumunozsala/roberta_bne_sentiment_analysis_es") model = AutoModelForSequenceClassification.from_pretrained("edumunozsala/roberta_bne_sentiment_analysis_es", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- e1b23b9d466bd4e597f30344e8c0dcc6760e1d91724361e167acd5fe859f478d
- Size of remote file:
- 2.42 kB
- SHA256:
- bb87587c012e747588b9f966920ccd2e150274f58a75251c398e565b1ab34a9a
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