Instructions to use tr3cks/3LabelsSentimentAnalysisSpanish with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use tr3cks/3LabelsSentimentAnalysisSpanish with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="tr3cks/3LabelsSentimentAnalysisSpanish")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("tr3cks/3LabelsSentimentAnalysisSpanish") model = AutoModelForSequenceClassification.from_pretrained("tr3cks/3LabelsSentimentAnalysisSpanish") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 219ae218333200dc76a1783c794a130d3f17b90ec5d500943313a6bd55b9263a
- Size of remote file:
- 439 MB
- SHA256:
- 08babc193147cf5ccbd849c03af10f211e40322f9e4bc175263e51f57b6e8f86
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