Sentence Similarity
sentence-transformers
PyTorch
Safetensors
Indonesian
bert
feature-extraction
text-embeddings-inference
Instructions to use LazarusNLP/congen-indobert-base with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- sentence-transformers
How to use LazarusNLP/congen-indobert-base with sentence-transformers:
from sentence_transformers import SentenceTransformer model = SentenceTransformer("LazarusNLP/congen-indobert-base") 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:
- b363a5af1b7a41b45e2e19a14ad7a38c53da37eaff2139af13e0faf5c9a0cfdc
- Size of remote file:
- 498 MB
- SHA256:
- ad4564a3774dbe82eeefe962f42daaf170f877615af0986aad2b3cab59aa890b
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.