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:
- 330b24bf163ce588cadb91cfa04461551643778dbbbfb936a77ed87ed44fa44c
- Size of remote file:
- 3.06 kB
- SHA256:
- d4e9d8ef48a4cdadb621c5fceedac639d3b43d6d6d050499dc85e5932540edd7
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