Text Classification
Transformers
PyTorch
Safetensors
Spanish
bert
sagemaker
beto
TextClassification
SentimentAnalysis
Eval Results (legacy)
text-embeddings-inference
Instructions to use edumunozsala/beto_sentiment_analysis_es with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use edumunozsala/beto_sentiment_analysis_es with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="edumunozsala/beto_sentiment_analysis_es")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("edumunozsala/beto_sentiment_analysis_es") model = AutoModelForSequenceClassification.from_pretrained("edumunozsala/beto_sentiment_analysis_es", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Commit History
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Fix Metric Typos (#1)
- Fix Metric Typos (1d86bcf67cb5a61dfe86cf2207d4c8b6076fa9b5) Co-authored-by: Matt Hyatt <mhyatt000@users.noreply.huggingface.co>a89bd5e
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