Sentence Similarity
sentence-transformers
Safetensors
bert
feature-extraction
text-embeddings-inference
Instructions to use JW451609703/bitext-llmft-labse with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- sentence-transformers
How to use JW451609703/bitext-llmft-labse with sentence-transformers:
from sentence_transformers import SentenceTransformer model = SentenceTransformer("JW451609703/bitext-llmft-labse") sentences = [ "That is a happy person", "That is a happy dog", "That is a very happy person", "Today is a sunny day" ] embeddings = model.encode(sentences) similarities = model.similarity(embeddings, embeddings) print(similarities.shape) # [4, 4] - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 15582a85ff44991f89c420bceffeb6ce9f9bfb74320b19fbe315c265eb997e95
- Size of remote file:
- 13.6 MB
- SHA256:
- 09216b42d2697b7b4a26ac05ff09ba8bf52dc19b896c5ceee8bbff9f39055322
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