Sentence Similarity
sentence-transformers
PyTorch
Transformers
Indonesian
bert
feature-extraction
text-embeddings-inference
Instructions to use firqaaa/indo-sentence-bert-base with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- sentence-transformers
How to use firqaaa/indo-sentence-bert-base with sentence-transformers:
from sentence_transformers import SentenceTransformer model = SentenceTransformer("firqaaa/indo-sentence-bert-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] - Transformers
How to use firqaaa/indo-sentence-bert-base with Transformers:
# Load model directly from transformers import AutoTokenizer, AutoModel tokenizer = AutoTokenizer.from_pretrained("firqaaa/indo-sentence-bert-base") model = AutoModel.from_pretrained("firqaaa/indo-sentence-bert-base") - Inference
- Notebooks
- Google Colab
- Kaggle
- Xet hash:
- c05a722e1ac900edc0d19f020e9580e97f6b9590d1ce2446decb35d97a894cb8
- Size of remote file:
- 498 MB
- SHA256:
- bed100daff583b23c3cbd210d22a46e44257544a5bcacd56a8bb57b03958e33b
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