Instructions to use DuboiJ/Sentiment_analysis_PI with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use DuboiJ/Sentiment_analysis_PI with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="DuboiJ/Sentiment_analysis_PI")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("DuboiJ/Sentiment_analysis_PI") model = AutoModelForSequenceClassification.from_pretrained("DuboiJ/Sentiment_analysis_PI", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- c236e702528894a182df7e0bc843f782c7cac3d3363741aa5616ea0dd39a435e
- Size of remote file:
- 499 MB
- SHA256:
- 8d30b43ba781e2f6a7393294e64fc002942fde18e74319e5c237966dfa414b89
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