Sentence Similarity
sentence-transformers
PyTorch
mpnet
feature-extraction
text-embeddings-inference
Instructions to use mathislucka/tat-model with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- sentence-transformers
How to use mathislucka/tat-model with sentence-transformers:
from sentence_transformers import SentenceTransformer model = SentenceTransformer("mathislucka/tat-model") 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
- Xet hash:
- cd606373b5b5b6b285726d215d8f8f79395cec77867a9aefa534d1ac94cafde7
- Size of remote file:
- 438 MB
- SHA256:
- 42fa283808f41ea8bdbf1720f2ccd3936f77cb5e23b59263ce3d2ce35fc2b0e2
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