Sentence Similarity
sentence-transformers
Safetensors
bert
feature-extraction
Generated from Trainer
dataset_size:133472
loss:SoftmaxLoss
Eval Results (legacy)
text-embeddings-inference
Instructions to use cassador/indobert-snli-v1 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- sentence-transformers
How to use cassador/indobert-snli-v1 with sentence-transformers:
from sentence_transformers import SentenceTransformer model = SentenceTransformer("cassador/indobert-snli-v1") sentences = [ "Dua tim anak-anak, yang satu berwarna hijau dan yang lainnya berwarna merah, bermain bersama dalam permainan Rugby saat hujan.", "Tiga orang berada di dalam perahu.", "seorang pria di atas sepeda", "Tim rugby anak-anak, merah versus hijau bermain di tengah hujan." ] embeddings = model.encode(sentences) similarities = model.similarity(embeddings, embeddings) print(similarities.shape) # [4, 4] - Notebooks
- Google Colab
- Kaggle
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