Sentence Similarity
sentence-transformers
Safetensors
Indonesian
bert
indonesian
semantic-similarity
stsb
embedding
fine-tuned
education
Eval Results (legacy)
text-embeddings-inference
Instructions to use eugene702/Automatic-Scoring with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- sentence-transformers
How to use eugene702/Automatic-Scoring with sentence-transformers:
from sentence_transformers import SentenceTransformer model = SentenceTransformer("eugene702/Automatic-Scoring") 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:
- 44172ecf4c4877c7c2cc5d5cff92caf43b726b3ec4a460521f0577bc5c802d49
- Size of remote file:
- 1.34 GB
- SHA256:
- 6417b2beae7cee1a3033e1486447f9a2b71f0506e35f8d736ceb2d1124e6df23
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