Sentence Similarity
sentence-transformers
PyTorch
mpnet
feature-extraction
text-embeddings-inference
Instructions to use AISE-TUDelft/python-summary-classifier with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- sentence-transformers
How to use AISE-TUDelft/python-summary-classifier with sentence-transformers:
from sentence_transformers import SentenceTransformer model = SentenceTransformer("AISE-TUDelft/python-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
Download pytorch_model.bin from AISE-TUDelft/python-summary-classifier: direct link, hf CLI and curl.
- Browser
- Download file 438 MB
-
https://huggingface.co/AISE-TUDelft/python-summary-classifier/resolve/main/pytorch_model.bin
- Command line
-
hf download hf://AISE-TUDelft/python-summary-classifier/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/AISE-TUDelft/python-summary-classifier/resolve/main/pytorch_model.bin
438 MB
- Xet hash:
- 57e3850206cf0beacab666785654c890de8261ad53c1057f3fc795711ffffefd
- Size of remote file:
- 438 MB
- SHA256:
- 2492cb3de66090cd3478889e81a8638bb3c6c64ffd85f187f254149b9e9e6e87
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