Instructions to use umich/bert-sentiment-nuclear with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use umich/bert-sentiment-nuclear with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="umich/bert-sentiment-nuclear")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("umich/bert-sentiment-nuclear") model = AutoModelForSequenceClassification.from_pretrained("umich/bert-sentiment-nuclear") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 8fa58db7e20faac2d43671fc2fe98cc958cca9cc376f8c7527add8f816cff75f
- Size of remote file:
- 4.98 kB
- SHA256:
- 9d47475ffee0b5284f0a78bd4815e5be5a7680659172cf6616d306a70792d7cd
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