Instructions to use tr3cks/SentimentAnalysis_BETO with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use tr3cks/SentimentAnalysis_BETO with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="tr3cks/SentimentAnalysis_BETO")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("tr3cks/SentimentAnalysis_BETO") model = AutoModelForSequenceClassification.from_pretrained("tr3cks/SentimentAnalysis_BETO", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Commit History
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upload flax model
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allow flax
de426f3
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commit from javi
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initial commit
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