Text Classification
Transformers
Safetensors
document-scoring
education
norwegian
nordic
🇪🇺 Region: EU
Instructions to use NbAiLab/nb-embed-edu-scorer with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use NbAiLab/nb-embed-edu-scorer with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="NbAiLab/nb-embed-edu-scorer")# pip install -U transformers accelerate # Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("NbAiLab/nb-embed-edu-scorer", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download tokenizer/tokenizer.json from NbAiLab/nb-embed-edu-scorer: direct link, hf CLI and curl.
- Browser
- Download file 9.48 MB
-
https://huggingface.co/NbAiLab/nb-embed-edu-scorer/resolve/main/tokenizer/tokenizer.json
- Command line
-
hf download hf://NbAiLab/nb-embed-edu-scorer/tokenizer/tokenizer.json
-
curl -L -o tokenizer.json https://huggingface.co/NbAiLab/nb-embed-edu-scorer/resolve/main/tokenizer/tokenizer.json
9.48 MB
File too large to display, you can check the raw version instead.