Feature Extraction
sentence-transformers
TensorBoard
Safetensors
sparse-encoder
sparse
splade
norwegian
scandinavian
information-retrieval
custom_code
Eval Results (legacy)
Instructions to use thivy/norbert4-base-splade-retrieval with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- sentence-transformers
How to use thivy/norbert4-base-splade-retrieval with sentence-transformers:
from sentence_transformers import SentenceTransformer model = SentenceTransformer("thivy/norbert4-base-splade-retrieval", trust_remote_code=True) sentences = [ "The weather is lovely today.", "It's so sunny outside!", "He drove to the stadium." ] embeddings = model.encode(sentences) similarities = model.similarity(embeddings, embeddings) print(similarities.shape) # [3, 3] - Notebooks
- Google Colab
- Kaggle
Upload README.md with huggingface_hub
Browse files
README.md
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### Training Datasets
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Retrieval-only datasets (
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### Hardware
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- **GPUs:** 2x NVIDIA H100
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### Training Datasets
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Retrieval-only datasets (query → document pairs):
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- **DDSC** - Nordic Embedding Training Data (~182K pairs, retrieval task only, NO/DA/SV)
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- **ETI** - Elektronisk Tjenesteinformasjon (~54K pairs, health/welfare domain, NO)
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- **NorQuAD** - Norwegian Question Answering (~3.8K pairs, NO)
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- **ScandiQA** - Scandinavian Question Answering (~20K pairs, NO/DA/SV)
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- **Supervised-DA** - Danish supervised retrieval pairs (~93K pairs, DA)
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**Total:** ~333K query-document pairs across Norwegian, Danish, and Swedish.
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### Hardware
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- **GPUs:** 2x NVIDIA H100
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