Text Classification
Transformers
PyTorch
Safetensors
Spanish
roberta
sagemaker
bertin
TextClassification
SentimentAnalysis
Eval Results (legacy)
text-embeddings-inference
Instructions to use edumunozsala/bertin_base_sentiment_analysis_es with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use edumunozsala/bertin_base_sentiment_analysis_es with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="edumunozsala/bertin_base_sentiment_analysis_es")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("edumunozsala/bertin_base_sentiment_analysis_es") model = AutoModelForSequenceClassification.from_pretrained("edumunozsala/bertin_base_sentiment_analysis_es", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- fc516e5c3526b09d29eb2a5eaba5601e8ec9b2ee510e98d4614fd7bca3c98c4c
- Size of remote file:
- 499 MB
- SHA256:
- dd21d6fcbe15c185977db5db5f28642f506028a120ebb69fc9447cea2d1ce394
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