Instructions to use Lauler/sentiment-classifier with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Lauler/sentiment-classifier with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="Lauler/sentiment-classifier")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("Lauler/sentiment-classifier") model = AutoModelForSequenceClassification.from_pretrained("Lauler/sentiment-classifier") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 0deed1ab3acf4db9dcf3e8d5561c9fcc5a99e88119920385b12b988024e5ab0e
- Size of remote file:
- 499 MB
- SHA256:
- a06382069f79d2e7715e085bb1da5c94d4f53ce17e8b4cc8e71b9341503d66ac
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