Instructions to use NTCAL/norbert2_sentiment_norec_6 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use NTCAL/norbert2_sentiment_norec_6 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="NTCAL/norbert2_sentiment_norec_6")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("NTCAL/norbert2_sentiment_norec_6") model = AutoModelForSequenceClassification.from_pretrained("NTCAL/norbert2_sentiment_norec_6") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 0028e54220da1bc84373eb09998a8a6adb029f179040e6ab4335f43a08015dd1
- Size of remote file:
- 1.42 GB
- SHA256:
- f5a63240f6b99e060dff17ff99d5bcbbc71c857574a3d073930653ef28825d9e
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