Sentence Similarity
sentence-transformers
Safetensors
Japanese
luke
linktransformer
tabular-classification
Instructions to use dell-research-harvard/lt-wikidata-comp-ja with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- sentence-transformers
How to use dell-research-harvard/lt-wikidata-comp-ja with sentence-transformers:
from sentence_transformers import SentenceTransformer model = SentenceTransformer("dell-research-harvard/lt-wikidata-comp-ja") 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
Updated model with better training and evaluation. Test and val data included as pickle files. Older Legacy files were removed to avoid confusion.
034082e - Xet hash:
- 353e922f67de1685d927b1eb1869f35688e34cf22e105b35c09f0559d78fda29
- Size of remote file:
- 1.61 MB
- SHA256:
- b5f9f9ad795ea65333e8fb33a54844f4fa0b0e0d1eb48147f8033f33cdb80c41
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