Feature Extraction
sentence-transformers
Safetensors
German
French
Italian
qwen3
sentence-similarity
swiss-law
legal-retrieval
dense-retrieval
text-embeddings-inference
Instructions to use ArneH/harrier-semantic-v1 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- sentence-transformers
How to use ArneH/harrier-semantic-v1 with sentence-transformers:
from sentence_transformers import SentenceTransformer model = SentenceTransformer("ArneH/harrier-semantic-v1") 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
- Xet hash:
- 8efc6183aedc48f043b076d5225021dabcc5ee09f1386e160e5780451415bb18
- Size of remote file:
- 11.4 MB
- SHA256:
- 6cf519278622d854311452949ee197ff7afb0fbb1e0fa16cc307a959d8e61764
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