Instructions to use thusken/nb-bert-base-user-needs with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use thusken/nb-bert-base-user-needs with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="thusken/nb-bert-base-user-needs")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("thusken/nb-bert-base-user-needs") model = AutoModelForSequenceClassification.from_pretrained("thusken/nb-bert-base-user-needs") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 942c96bd08e8059f5a516152d5ff0ca7ce2cf053e121ca7f8969b44c148ab93d
- Size of remote file:
- 712 MB
- SHA256:
- de1c79f804196a2fe496dd6b38108fbe4b4614c99642d1f6ecddad5d81f469d2
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