Text Classification
Transformers
PyTorch
Safetensors
Northern Sami
Norwegian
English
bert
sami relevant
Instructions to use NbAiLab/nb-bert-base-sami-relevant with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use NbAiLab/nb-bert-base-sami-relevant with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="NbAiLab/nb-bert-base-sami-relevant")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("NbAiLab/nb-bert-base-sami-relevant") model = AutoModelForSequenceClassification.from_pretrained("NbAiLab/nb-bert-base-sami-relevant", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Update config.json
Browse files- config.json +9 -0
config.json
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@@ -3,6 +3,15 @@
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"architectures": [
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"BertForSequenceClassification"
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],
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"attention_probs_dropout_prob": 0.1,
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"directionality": "bidi",
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"gradient_checkpointing": false,
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"architectures": [
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"BertForSequenceClassification"
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],
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+
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"id2label": {
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"0": "Not Sami Relevant",
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"1": "Sami Relevant",
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},
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"label2id": {
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"Not Sami Relevant": 0,
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"Sami Relevant": 1
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},
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"attention_probs_dropout_prob": 0.1,
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"directionality": "bidi",
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"gradient_checkpointing": false,
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