Instructions to use wangyh6/sentiment-analysis with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use wangyh6/sentiment-analysis with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="wangyh6/sentiment-analysis")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("wangyh6/sentiment-analysis") model = AutoModelForSequenceClassification.from_pretrained("wangyh6/sentiment-analysis") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 9a5cb1c4bb7c03c1461bdf067ae30bbe966d747f9e5a45141a73cc3bfd952fa9
- Size of remote file:
- 268 MB
- SHA256:
- 61afb985df6fbe77fd84138129481f0a4444c02893782984e330f874f43cee4b
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