Instructions to use NTCAL/norbert2_sentiment_norec_4 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use NTCAL/norbert2_sentiment_norec_4 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="NTCAL/norbert2_sentiment_norec_4")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("NTCAL/norbert2_sentiment_norec_4") model = AutoModelForSequenceClassification.from_pretrained("NTCAL/norbert2_sentiment_norec_4") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 135b18389209e158f653bd449296c7a14b660b0a0dfc079cb57848f2f58b3411
- Size of remote file:
- 3.52 kB
- SHA256:
- 7b79e73347a56096652401c7f547bcbddf5539942578979dfe6a73d05ecfdf06
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