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
Librarian Bot: Add base_model information to model
#2
by librarian-bot - opened
README.md
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- f1
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- precision
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- recall
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model-index:
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- name: nb-bert-base-user-needs
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results: []
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- f1
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- precision
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- recall
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base_model: NbAiLab/nb-bert-base
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model-index:
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- name: nb-bert-base-user-needs
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results: []
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