Instructions to use Tanor/BERTicSENTNEG4 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Tanor/BERTicSENTNEG4 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="Tanor/BERTicSENTNEG4")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("Tanor/BERTicSENTNEG4") model = AutoModelForSequenceClassification.from_pretrained("Tanor/BERTicSENTNEG4", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 35590bbb713856640bc9caf1e4aaff96562589ce5e3fbb7b5500ba5606b6eda3
- Size of remote file:
- 443 MB
- SHA256:
- b7a9ac8561bdc0badcb39f86da9c32c99a04d8fc664cd07e5f2ef370c5921aff
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