Sentence Similarity
sentence-transformers
PyTorch
mpnet
feature-extraction
text-embeddings-inference
Instructions to use AISE-TUDelft/java-summary-classifier with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- sentence-transformers
How to use AISE-TUDelft/java-summary-classifier with sentence-transformers:
from sentence_transformers import SentenceTransformer model = SentenceTransformer("AISE-TUDelft/java-summary-classifier") sentences = [ "That is a happy person", "That is a happy dog", "That is a very happy person", "Today is a sunny day" ] embeddings = model.encode(sentences) similarities = model.similarity(embeddings, embeddings) print(similarities.shape) # [4, 4] - Notebooks
- Google Colab
- Kaggle
Adding `safetensors` variant of this model
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by SFconvertbot - opened
- model.safetensors +3 -0
model.safetensors
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version https://git-lfs.github.com/spec/v1
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oid sha256:68103c51c2978272b505e4ae746441f72225b0d5c4eceef4f8abe082dbb7e57f
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size 437971872
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