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
File size: 205 Bytes
e587e62 | 1 2 3 4 5 6 7 8 9 10 | {
"__version__": {
"sentence_transformers": "4.1.0",
"transformers": "4.52.4",
"pytorch": "2.6.0+cu124"
},
"prompts": {},
"default_prompt_name": null,
"similarity_fn_name": "cosine"
} |